Neuropsychological Research: A Review

Neuropsychological Research

In a broad sense, neuropsychology stands for the branch of brain sciences that aims to understand how the structure and function of the brain relate to specific cognitive and psychological processes. The idea of developing a research field somewhere between neurology and cognitive psychology emerged in the 1960s as a result of studies conducted by both disciplines which, although using different methodologies and tools, were analysing the same issues. Neuropsychology particularly puts emphasis on the clinical and experimental study of the cognitive effects of brain injury or neurological diseases, taking models of normal cognitive functioning into account. Neuropsychological Research: A Review provides a meticulous overview of what has been achieved in the field of cognitive neuropsychology from its early beginnings in the 1960s and 1970s to the present day. Authors include some of the pioneers involved in the genesis of neuropsychology as an independent and distinct field of neuroscience. The comprehensive coverage includes language disorders, skilled movement disorders, recognition disorders, attentional and executive disorders, visuo-perceptual disorders, memory disorders, and neurodegenerative diseases. This fascinating text forms an enjoyable tribute to the rich heritage of neuropsychology, and will be essential reading for researchers and students of neuropsychology, clinical psychology, cognitive psychology, and behavioural neuroscience. Peter Mariën is a Clinical Neurolinguist in the Department of Neurology at ZNA Middelheim Hospital, Antwerp, Belgium. He is Professor of Neurolinguistics and Psycholinguistics at Vrije Universiteit Brussels and the University of Ghent. His main area of research is in the field of clinical neurolinguistics and neuropsychology. Jubin Abutalebi is a Cognitive Neurologist and Senior Researcher at the Faculty of Psychology of the Vita-Salute San Raffaele University in Milan, Italy. His research interests lie in the area of clinical neuropsychology and, specifically, language disorders in theory and practice.

Neuropsychological Research A Review

Edited by Peter Mariën and Jubin Abutalebi

First published 2008 by Psychology Press 27 Church Road, Hove, East Sussex BN3 2FA Simultaneously published in the USA and Canada by Routledge 270 Madison Avenue, New York, NY 10016 This edition published in the Taylor & Francis e-Library, 2008. “To purchase your own copy of this or any of Taylor & Francis or Routledge’s collection of thousands of eBooks please go to www.eBookstore.tandf.co.uk.” Psychology Press is an imprint of the Taylor & Francis Group, an informa business Copyright © 2008 Psychology Press All rights reserved. No part of this book may be reprinted or reproduced or utilized in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. The publisher makes no representation, express or implied, with regard to the accuracy of the information contained in this book and cannot accept any legal responsibility or liability for any errors or omissions that may be made. The publication has been produced with paper manufactured to strict environmental standards and with pulp derived from sustainable forests. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Neuropsychological research : a review / [edited by] Peter Mariën and Jubin Abutalebi. p. cm. Includes bibliographical references and index. ISBN 978-1-84169-620-1 (hardcover) 1. Neuropsychology. I. Mariën, Peter, 1962– II. Abutalebi, Jubin, 1969– [DNLM: 1. Neuropsychology–methods. 2. Brain Diseases– physiopathology. 3. Cognition. 4. Nervous System Diseases– physiopathology. WL 103.5 N4935 2008] QP360.N49363 2008 612.8–dc22 2007025344 ISBN 0-203-93890-9 Master e-book ISBN

ISBN: 978-1-84169-620-1 (hbk)

This book is dedicated to our scientific mentor, inspiring colleague, and dear friend, Professor Luigi Amedeo Vignolo.

This photograph was taken on 17 September 2005, during a “festa” for Luigi’s retirement, organized by Anna (“Mimi”) Basso and Stefano F. Cappa near Lerici, Italy. © Giuseppe Vallar.

Contents

Contributors

xi

Introduction

1

JUBIN ABUTALEBI AND PETER MARIËN

Homage to Luigi Amedeo Vignolo

7

ARTHUR L. BENTON

Dedication to a pioneer in neuropsychology

9

ENNIO DE RENZI

SECTION I

Approaching the brain 1 A multiplicity of intelligences

15 17

HOWARD GARDNER

2 Neural circuitry underlying language

25

MICHAEL PETRIDES AND DEEPAK N. PANDYA

3 Structural and functional neuroimaging in neuropsychology: a concise overview JUBIN ABUTALEBI, LISA BARTHA DOERING, PASQUALE ANTHONY DELLA ROSA, AND PETER MARIËN

51

viii Contents SECTION II

Language disorders 4 Information-processing models of aphasia: updating the diagram makers

73

75

KENNETH M. HEILMAN

5 The impact of right-hemisphere lesions on language abilities: theoretic and clinical perspectives

93

YVES JOANETTE, ANA INÉS ANSALDO, KARIMA KAHLAOUI, AND ANDRÉ ROCH LECOURS

6 Acquired dyslexia and dysgraphia

113

RIA DE BLESER AND CLAUDIO LUZZATTI

7 Developmental dyslexia: from neuropsychology to genetics, and back again

127

ALBERT M. GALABURDA, JOSEPH LOTURCO, AND GLENN D. ROSEN

8 Aphasia recovery: neural mechanisms

137

STEFANO F. CAPPA AND JUBIN ABUTALEBI

9 Aphasia rehabilitation

147

ANNA BASSO

SECTION III

Skilled movement, music, and number-processing disorders

159

10 The forelimb apraxias

161

KENNETH M. HEILMAN, LESLIE J. GONZALEZ ROTHI, AND BRENDA HANNA-PLADDY

11 Should we make aphasic patients sing?

185

SYLVIE HÉBERT, ISABELLE PERETZ, AND AMÉLIE RACETTE

12 The neuropsychology of calculation and number processing XAVIER SERON

201

Contents

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SECTION IV

Modality-specific recognition disorders

229

13 Perceptual categorization: language and thought

231

JULES DAVIDOFF

14 Visual agnosia

249

H. BRANCH COSLETT

15 Auditory agnosia

267

MARIE DI PIETRO, MARINA LAGANARO, AND ARMIN SCHNIDER

16 Somaesthetic recognition disorders

285

GABRIELLA BOTTINI AND MARTINA GANDOLA

SECTION V

Neglect, attentional, and executive disorders

305

17 Subcortical neglect

307

GIUSEPPE VALLAR

18 Neuropsychology of attention

331

MICHAEL I. POSNER

19 Measuring human cognition online by electrophysiological methods: the case of selective attention

349

ANNA CHRISTINA NOBRE AND LAETITIA SILVERT

20 The frontal lobe: executive, emotional, and neurological functions

379

PAUL J. ESLINGER

SECTION VI

Memory disorders and neurodegenerative diseases

409

21 Memory: structure, function, and dysfunction

411

OLIVIER PIGUET AND SUZANNE CORKIN

x

Contents

22 Effects of aging and dementia on memory

437

GIANFRANCO DALLA BARBA, FRANÇOIS BOLLER, AND DOROTHÉE RIEU

23 Semantic dementia: the story so far

471

JONATHAN KNIBB AND JOHN R. HODGES

24 Frontal lobe dysfunction across diagnostic dementia categories

491

SEBASTIAAN ENGELBORGHS, PETER MARIËN, AND PETER P. DE DEYN

SECTION VII

Concluding remarks Concluding remarks

511 513

PETER MARIËN AND JUBIN ABUTALEBI

Author index Subject index

515 541

Contributors

Jubin Abutalebi Centre for Cognitive Neurosciences, Vita-Salute San Raffaele University, Via Olgettina 58, 20132 Milan, Italy, and Interdisciplinary Center for Cognitive Studies, Faculty for Human Sciences, University of Potsdam, Potsdam, Germany Ana Inés Ansaldo Centre de recherche, Institut universitaire de gériatrie de Montréal, 4565 chemin Queen Mary, Montréal H3W 1W5, and École d’orthophonie et d’audiologie, Faculté de médecine, Université de Montréal, Canada Anna Basso Institute for Neurological Sciences, University of Milan, Via F. Sforza 35, 20122 Milan, Italy Arthur L. Benton Department of Neurology and Psychology at the University of Iowa (the author died on 26 December 2006) François Boller Inserm Unit 610, Pavillon Claude Bernard, 47, boulevard de l’hôpital, 75013 Paris, France Gabriella Bottini University of Pavia, Piazza Botta 6, 27100 Pavia, and Cognitive Neuropsychology Laboratory, Neuroscience Department, Niguarda Hospital, Milan, Italy Stefano F. Cappa Department of Neuropsychology, Vita-Salute San Raffaele University-DIBIT, Via Olgettina 58, 20132 Milan, and Department of Neurology, San Raffaele Turro Hospital, Milan, Italy Suzanne Corkin Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 46–5121, Cambridge, MA 02139, USA H. Branch Coslett Department of Neurology, University of Pennsylvania School of Medicine, 3400 Spruce Street, Philadelphia, PA 19104, USA Jules Davidoff Department of Psychology, Goldsmiths College, University of London, Lewisham Way, London SE14 6NW, UK Gianfranco Dalla Barba Inserm Unit 610, Pavillon Claude Bernard, 47, boulevard de l’hôpital, 75013 Paris, France

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Contributors

Ria De Bleser Department of Cognitive Neurolinguistics, University of Potsdam, PF 601553, D-14415 Potsdam, Germany Peter P. De Deyn Department of Neurology and Memory Clinic, Middelheim General Hospital (ZNA), Lindendreef 1, B-2020 Antwerp, and Laboratory of Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium Pasquale Anthony Della Rosa Functional Brain Mapping Laboratory, Neurology Department, Geneva University Hospitals, 24 Rue Micheli-duCrest, 1211 Geneva 14, and Laboratory of Experimental Psycholinguistics, Université de Genève, Geneva, Switzerland Ennio De Renzi University of Modena, Modena, Italy Marie Di Pietro Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals of Geneva, Av. de Beau-Séjour 26, CH-1211 Geneva 14, Switzerland Lisa Bartha Doering Department of Psychosomatics and Psychotherapy, University of Münster, Münster, Germany Sebastiaan Engelborghs Department of Neurology and Memory Clinic, Middelheim General Hospital (ZNA), Lindendreef 1, B-2020 Antwerp, and Laboratory of Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium Paul J. Eslinger Departments of Neurology, Neural and Behavioral Sciences, Pediatrics, and Radiology, Center for NMR Research, Penn State Concussion Program, and Neurorehabilitation Unit, Penn State University College of Medicine and Milton S. Hershey Medical Center, P.O. Box 850, Hershey, PA 17033–0850, USA Albert M. Galaburda Harvard Medical School, Division of Behavioral Neurology and Memory Disorders, and Beth Israel Deaconess Medical Center, 330 Brookline Avenue, K-274, Boston, MA 02215, USA Martina Gandola University of Pavia, Piazza Botta 6, 27100 Pavia, Italy Howard Gardner Harvard Graduate School of Education, 14 Appian Way, 201 Larsen Hall, Cambridge, MA 02138, USA Leslie J. Gonzalez Rothi Brain Rehabilitation Research Center, Veterans Administration Medical Center and University of Florida College of Medicine, Gainesville, FL 32610, USA Brenda Hanna-Pladdy Landon Center on Aging and Department of Neurology, University of Kansas Medical Center, Kansas City, KS, USA Sylvie Hébert International Laboratory for Brain, Music, and Sound Research (BRAMS), École d’orthophonie et d’audiologie, Université de Montréal, BRAMS-Pavillon 1420 Mont-Royal, Montreal, Canada H3C 3J7

Contributors

xiii

Kenneth M. Heilman Department of Neurology, Veterans Administration Medical Center and University of Florida College of Medicine, Gainesville, FL 32610, USA John R. Hodges MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, UK Yves Joanette Centre de recherche, Institut universitaire de gériatrie de Montréal, 4565 chemin Queen Mary, Montreal H3W 1W5, and École d’orthophonie et d’audiologie, Faculté de médecine, Université de Montréal, Canada Karima Kahlaoui Centre de recherche, Institut universitaire de gériatrie de Montréal, 4565 chemin Queen Mary, Montreal H3W 1W5, and École d’orthophonie et d’audiologie, Faculté de médecine, Université de Montréal, Canada Jonathan Knibb MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, UK Marina Laganaro Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals of Geneva, Av. de Beau-Séjour 26, CH-1211 Geneva 14, Switzerland André Roch Lecours Centre de recherche, Institut universitaire de gériatrie de Montréal, and École d’orthophonie et d’audiologie, Faculté de médecine, Université de Montréal, Canada (the author died on 12 June 2005) Joseph LoTurco Department of Physiology and Neurobiology, University of Connecticut, 75 North Eagleville Road, U3156, Storrs, CT 06268–3156, USA Claudio Luzzatti Dipartimento di Psicologia, Università di Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, I-20126 Milan, Italy Peter Mariën Department of Neurology, ZNA AZ Middelheim, Lindendreef 1, B-2020 Antwerp; Vakgroep Taal en Letterkunde, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels; and Faculty of Medicine, University of Ghent, Belgium Anna Christina Nobre Brain and Cognition Laboratory, Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford OX1 3UD, UK Deepak N. Pandya Departments of Anatomy and Neurology, Boston University School of Medicine, Boston, MA 02118, and Harvard Neurological Unit, Beth Israel Hospital, Boston, MA 02215, USA Isabelle Peretz International Laboratory for Brain, Music, and Sound Research (BRAMS), Psychology Department, BRAMS-Pavillon 1420 Mont-Royal, Montreal, Canada H3C 3J7

xiv

Contributors

Michael Petrides Montreal Neurological Institute, McGill University, 3801 University Street, Montreal H3A 2B4, and Department of Psychology, McGill University, 1205 Dr. Penfield Avenue, Montreal, Canada H3A 1B1 Olivier Piguet Prince of Wales Medical Research Institute, Barker Street, Randwick NSW 2031, Australia Michael I. Posner Department of Psychology, 1227 University of Oregon, Oregon, USA Amélie Racette International Laboratory for Brain, Music, and Sound Research (BRAMS), Psychology Department, BRAMS-Pavillon 1420 Mont-Royal, Montreal, Canada H3C 3J7 Dorothée Rieu Inserm Unit 610, Pavillon Claude Bernard, 47, boulevard de l’hôpital, 75013 Paris, France Glenn D. Rosen Department of Neurology (Neuroscience), Harvard Medical School, and Dyslexia Research Laboratory, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, K-274 Boston, MA 02215, USA Armin Schnider Division of Neurorehabilitation, Department of Clinical Neurosciences, University Hospitals of Geneva, Av. de Beau-Séjour 26, CH-1211 Geneva 14, Switzerland Xavier Seron Université Catholique de Louvain, Louvain-la-Neuve, Belgium Laetitia Silvert University of Clermont-Ferrand (UMR CNRS 6024) and Université Blaise Pascal, LAPSCO–UMR CNRS 6024, 34, Avenue Carnot, 63037 Clermont-Ferrand Cedex, France Giuseppe Vallar Università degli Studi di Milano-Bicocca, Dipartimento di Psicologia, Edificio U6, Piazza dell’Ateneo Nuovo 1, 20126-Milan, and IRCCS Istituto Auxologico Italiano, Milan, Italy

Introduction Jubin Abutalebi and Peter Mariën

Neuropsychological Research originated as a Festschrift for Professor Luigi Amedeo Vignolo, an extraordinary behavioural neurologist, excellent neuroscientist, and dedicated teacher, who has done excellent work on various aspects of neuropsychology. The book was conceived as a project to stimulate the understanding of how neuropsychology has developed since Norman Geschwind’s influential reintroduction of the Wernicke–Lichtheim model in the 1960s to a modern multifaceted and most intriguing discipline of neuroscience. We believe that the work and writings of the pioneers in experimental and cognitive neuropsychology, and the scholars who were educated by them, may generate a lasting appreciation for the sense of wonder that drives scientific efforts. In a broad sense, neuropsychology is the branch of brain sciences which investigates how brain structure and function relate to specific cognitive and psychological processes. The discipline particularly emphasizes the clinical and experimental investigation of the impact of brain injury on cognitive processes, while taking models of normal cognitive functioning into account. Modern neuropsychology emerged during the 1960s following a series of influential studies which established a reliable basis for the study of brain– behaviour relationships. It is generally accepted that scientific research into the neural correlates of cognitive functions derives from the early innovative anatomoclinical observations of the French surgeon Paul Broca and the findings of the German neurologist Carl Wernicke during the second half of the nineteenth century. Apart from their historical importance, these hallmark studies marked the early beginnings of neuropsychology as a scientific discipline and they had a number of crucial implications for the understanding of brain–behaviour relationships. Firstly, these studies revealed that a variety of cognitive processes can sustain isolated damage, which indicates that these processes may be subserved by distinct and independent cognitive and neural mechanisms. Secondly, the early insights gave rise to the view that cognitive processes and their underlying neural substrate might be localized in specific, non-contiguous areas of the brain. Although both of these claims have to some extent remained controversial, they refocused attention on brain injury

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as a potentially fruitful way to explore the relationship between brain and behaviour. During the 1960s, information-processing paradigms became the predominant method to investigate cognitive processes. This approach provided an important theoretical framework for neuropsychology. It not only allowed a better insight into the functional role of particular brain regions but also provided a deeper understanding of brain injury in abstract terms, such as impairment of the information-processing abilities within a larger cognitive system. The term “cognitive neuropsychology” emerged to denote these new approaches in the study of brain–behaviour mechanisms. In the genesis of cognitive neuropsychology, two parent fields played a crucial role: psychology and neuroscience. In general, traditional psychologists investigated overall principles and properties of cognitive processes, such as perception, attention, problem solving, language production (speaking and writing), and comprehension (listening and reading), with little interest in the functional neuroanatomy that supported these functions. On the other hand, neuroscientists from different backgrounds investigated the nervous system, focusing on relatively low-level mechanisms within a specific system. Since the first efforts to establish an integrated approach to mind and brain relationships in the 1960s and 1970s, neuropsychology has boomed as a research area, by combining segregated approaches to understand the basic rules underlying the functional organization of the brain. While neuroscience made enormous progress in understanding the neural system, psychology created an interest in the characteristics of intelligent systems, in nature or in computers. In particular, cognitive psychologists focused attention to a detailed analysis of mental events. From the 1960s onward, neuroscience, psychology, and linguistics joined forces to study how the human brain computes particular aspects of higher cognitive functioning. The approach had become multidisciplinary. In addition, these research areas relied on new assessment methods and innovative neuroimaging techniques that allowed in vivo visualization of the structural anatomy of the human brain for the first time. Neuropsychologists are particularly interested in how the brain completes very complex tasks such as perception, memory, attention, problem solving, and language. Using a combination of theoretical and methodological techniques from a variety of related disciplines, neuropsychology attempts to understand the complex dynamics of the working brain. The study of the human brain has recently confirmed that each cognitive act involves a close interaction of distinct neural networks. This equally applies to thinking, reading and listening to music. This was achieved by the need for knowledge about brain–behaviour relationships and the tremendous improvement of technology, such as advanced neuroimaging and neurophysiological techniques. It is clear to most neuroscientists that progress in neuropsychology is just opening up the field of brain and mind sciences. So far, progress has been quite impressive but it is far from completed. The future will certainly bring

Introduction

3

more powerful and precise techniques, the application of which will open up new avenues for research. The founders of modern neuropsychology strongly promoted the communication of knowledge to future generations. Professor Luigi Amedeo Vignolo, enthusiastically and patiently communicated his meticulous dedication to the study of human brain functions, inspiring many disciples in many different countries. His desire to stimulate greater knowledge guided us to edit this book in order to share the rich heritage of neuropsychology with others. Neuropsychological Research is organized as follows. Arthur L. Benton, who sadly passed away in December 2006, enthusiastically accepted our invitation to pay homage to his friend Professor Vignolo. Benton provides an interesting account of the developments in Italian neuropsychology in the 1960s and 1970s. Ennio De Renzi discusses the contribution of Vignolo to the field of neuropsychology and gives some interesting facts about the people who implemented the basic framework on which an important tradition of cognitive neuropsychology was founded. The first section of the book is called “Approaching the Brain”. There are many different approaches to the study of cognitive functions. This section introduces three entirely different ways to approach cognition. Chapter 1 by Howard Gardner updates his excellent Scientific American paper from 1998, recasting the subject of “intelligence” from a psychometric IQ to a broader range of computational capabilities. Gardner underlines how the discoveries in neuropsychology have emphasized the theory of multiple intelligences. Chapter 2 by Michael Petrides and Deepak N. Pandya provides a neuroanatomical description of the brain circuits that support language functions. This chapter summarizes a wide range of research that does not usually appear in neuropsychology handbooks and offers an expert description of the histological brain anatomy underlying language. It is an authoritative comparison of work on monkeys and man that relates to the role of neural circuits in language processing. Chapter 3 by Jubin Abutalebi, Lisa Bartha Doering, Pasquale Anthony Della Rosa, and Peter Mariën concisely discusses neuroimaging in neuropsychology and includes a guide on how to carry out a functional neuroimaging experiment. Section II of Neuropsychological Research focuses on language disorders. Because of the importance of the study of language in the history of neuropsychology, this section is the most elaborate one. In Chapter 4, Kenneth M. Heilman provides an innovative insight into the diagram makers and their models. It presents an interesting theory of how a modified and updated Wernicke–Kussmaul–Lichtheim model can account for much of the extensive aphasic symptomatology that has been described in recent years. Chapter 5 by Yves Joanette, Ana Inés Ansaldo, Karima Kahlaoui, and the late André Roch Lecours provides a survey of research on the role of the right hemisphere in language functions. This chapter summarizes current knowledge about right-hemisphere language functions. It attempts to bring right-hemisphere

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language impairments under the umbrella of “aphasiology”. This view is substantiated by sound clinical evidence, and some theoretical and functional justification is given. In Chapter 6, Ria De Bleser and Claudio Luzzatti discuss acquired disorders of reading and writing. It presents a comprehensive survey of two different approaches to the contemporary study of acquired dysfunctions of reading and writing: the classical approach that prevailed until the early 1990s and the cognitive approach. In Chapter 7, Albert M. Galaburda, Joseph LoTurco, and Glenn D. Rosen focus on the neuropsychological and genetic aspects of developmental dyslexia. This chapter is particularly relevant for cognitive neuropsychologists interested in reading and orthography: it is a particularly insightful review of neuroanatomical, genetic, and behavioural aspects. In Chapter 8, Stefano F. Cappa and Jubin Abutalebi illustrate the main principles of the neural reorganization that may take place after damage to the language areas. In Chapter 9, Anna Basso reviews the principles of aphasia rehabilitation and asks some important questions that are often ignored in efficacy studies, such as the effects of the amount of therapy provided. The third section of the book is dedicated to the neuropsychology of skilled movement disorders such as apraxia and disorders of digit and music processing. In Chapter 10, Kenneth M. Heilman, Leslie J. Gonzalez Rothi, and Brenda Hanna-Pladdy present an important overview of the historical and contemporary issues into forelimb apraxia. Sylvie Hébert, Isabelle Peretz, and Amélie Racette report on the use of music in the rehabilitation of aphasic patients in Chapter 11. These experts examine the old idea that aphasic patients can use the intact ability to sing in language treatment. This chapter presents an excellent review of issues of hemispheric preference. The historical perspective and the background on normal singing are a useful basis for discussion. In the last chapter of this section (Chapter 12), Xavier Seron, one of the world’s leading experts in the field, discusses the neuropsychology of number processing and the clinical aspects of acalculia. This is a very comprehensive and accessible account with useful historical notes. The fourth section of Neuropsychological Research is dedicated to the neuropsychology of modality-specific recognition disorders. In Chapter 13, Jules Davidoff presents useful historical insights and a thorough overview of perceptual categorization deficits. The chapter relies on a detailed examination of research in which the subject LEW has featured. Chapter 14 by H. Branch Coslett discusses visual agnosia. This chapter presents fascinating data, and contains interesting information about the historical background. Chapter 15 is a comprehensive overview of auditory agnosia by Marie Di Pietro, Marina Laganaro, and Armin Schnider. In Chapter 16 of this section, Gabriella Bottini and Martina Gandola review the somaesthetic recognition disorders, which are not usually covered in neuropsychology texts in any detail. Section V of the book examines neuropsychological issues such as neglect and attentional and executive disorders. In Chapter 17, Giuseppe

Introduction

5

Vallar discusses subcortical neglect, seldom covered in neuropsychology texts. This chapter presents an interesting account of the development of Italian neuropsychology. Chapter 18 is an excellent contribution by Michael I. Posner to the neuropsychology of attention: it discusses his early imaging work in St Louis (USA) and provides a historical background. The application of electrophysiology as an online method to measure attentional mechanisms by Anna Christina Nobre and Laetitia Silvert (Chapter 19) expands on selective attention. A historical sketch is followed by a well-formulated description of the contribution and limitations of EEG techniques. In the last chapter of this section (Chapter 20), Paul J. Eslinger presents an exhaustive survey of the role of the frontal lobe in executive, emotional, and neurological functions. The detail on frontal lobe structure and function is excellent, covering clinical and experimental work. Section VI of Neuropsychological Research deals with the branch of human psychology that may be considered the primary source of neuropsychology: the study of human memory systems and related disorders. The section starts with an introduction (Chapter 21) on structure, function, and dysfunction of memory by Olivier Piguet and Suzanne Corkin. It discusses memory in art and popular culture, and presents an excellent review of models of memory and imaging studies of memory and memory impairments. Chapter 22 by Gianfranco Dalla Barba, François Boller, and Dorothée Rieu discusses the effects of ageing on human memory functioning and, hence, dementia. The chapter contains an excellent discussion of memory in normal ageing and dementia. Chapter 23 by Jonathan Knibb and John R. Hodges reviews semantic dementia, a type of dementia that has recently attracted a great deal of attention in neuropsychological research. This is another expert review of the status of semantic dementia, with a very useful explanation of its history and its cognitive, behavioural, and neurological features. The authors differentiate between various forms of progressive aphasia and dementia, paying attention to the grey areas as well. The figures illustrating proposed relationships between conditions are particularly clear and useful. Finally, in the last chapter of the volume, Sebastiaan Engelborghs, Peter Mariën, and Peter P. De Deyn review the clinical, behavioural, and neuropsychological correlates of frontal lobe features in several diagnostic dementia categories and discuss how the pathophysiology of frontal lobe symptoms in dementia can be studied. We are immensely grateful for the impressive range of eminent authors who expressed their enthusiasm for the initiative to honour Professor Vignolo in an entertaining, informative, comprehensive, and very up-to-date contribution. The product of their efforts is a thoroughly comprehensive collection of chapters covering the mainstream and emerging issues in current neuropsychology. In addition, the authors provided a historical sketch of their topic, citing original studies and theoretical developments, from which readers may benefit greatly. We wish to thank Professor Jo Verhoeven from the department of Communication Sciences at City University, London for

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his all-round support and constructive criticism during the entire production of the volume. We also acknowledge the editorial assistance provided by Hanne Baillieux, Hyo-Jung De Smet, Psychology Press, as well as the anonymous reviewers, whose favourable comments encouraged us throughout this project. But most of all we are grateful to Professor Vignolo, whose exceptionally warm personality, great wisdom, and tremendous knowledge inspired us in many aspects of our professional and personal life. To him we dedicate this book.

Homage to Luigi Amedeo Vignolo

Time: 1961; place: Rome; occasion: International Congress of Neurology. I had been appointed rapporteur of the session on aphasia at the Congress. This involved summarizing the contents of some 24 papers on aphasia in the course of 110 minutes, allowing perhaps 4 minutes per paper. This tedious recital was intended to accomplish one basic purpose, namely, to record for posterity that the paper had indeed been presented at the Congress and was an official part of the program. Rebelling against this dismal prospect, I decided to break bounds and try to make the session more interesting. I selected three papers that seemed to me particularly timely in the field of aphasia. The first was a report from the Genoa Clinic on the use of acetylcholine to alleviate the symptoms of aphasia; the second was a report by Davis Howes and Norman Geschwind of the Massachusetts Institute of Technology on a stylistic analysis of aphasic speech. The third was a report by two young researchers of the Milan Clinic on a new test of language comprehension or language understanding for patients with extremely limited vocabularies; they called it “the Token Test”. At that time, Ennio De Renzi’s English was somewhat limited; in contrast, Luigi Vignolo, who spent some of the World War II years as a high school student in Connecticut, spoke excellent English. Consequently, I discussed the details of the presentation of the Token Test with Luigi. Three years later, in 1964, Professor Gildo Gastaldi invited me to conduct a 2-month course on neuropsychology at his clinic in Milan (there was no doubt that Professor Gastaldi’s invitation was the result of the maneuvers of De Renzi and Vignolo). This introductory course marked the onset of the study of neuropsychology in Italy, the birth of the renowned Italian school of neuropsychology. From that summer of 1964 onward, I have had a continuing and ever deepening friendship and collaboration with Luigi Vignolo and Ennio De Renzi. I count this association as one of the most gratifying experiences of my professional career. It gives me great pleasure to salute Luigi and Ennio. Arthur L. Benton Evanston, Illinois, USA 16 October 2004

Dedication to a pioneer in neuropsychology Ennio De Renzi

I first met Luigi Amedeo Vignolo in the late 1950s in the wards of the neurology department of the University of Milan, which he was attending in his sixth year as a medical student, and I as a doctor and research assistant. He had just asked Professor Gildo Gastaldi, chief of the department, for a subject for his thesis, and I was entrusted with the task of assisting the candidate. In Italian universities, a thesis was, and still is, the final step required to obtain a degree in medicine, and it can be either bibliographic or experimental, that is, a review of the literature on a given topic or a clinical investigation aimed at clarifying a controversial issue. The latter type was valued more highly and considered appropriate for a bright student. It was usually conducted with the assistance of a tutor, already experienced in research, and so it came about that we had to work together. Luigi stood out among the students of his year for his easy and elegant manners, his familiarity with foreign languages and countries—an asset shared by few in those days—and a genuine curiosity about the relationship between brain and mind. He was born in Monte Carlo, where he spent his early years, attended high school in Genova, spent a year in the USA, and then matriculated in medicine at the faculty of São Paulo in Brazil. Consequently, he had a good command of French, English, and Portuguese. We concurred that an attractive area of investigation for his thesis would be the study of language disorders, although we soon realized that it was hard for people with little experience to find a safe way of approaching such an entangled issue. Luigi had read the Brazilian translation of a test for aphasia, originally devised by Wepman and Halstead for American patients, and he proposed to prepare an Italian version of it. We agreed that its administration to left-brain-damaged patients would serve the dual purpose of providing a useful instrument for future investigation and improving our knowledge of aphasia. Although the test eventually turned out to be in need of radical revision and ceased to be used by us, the net result of the hours passed in discussing how to classify the patients’ responses to its items was positive, as we got to learn the intricacy of language disorders. Vignolo took his degree in medicine in 1960 and stayed in the department of neurology of Milan, where he became one of the outstanding members of

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a team of enthusiastic, young investigators of the behavioural consequences of brain lesions, known as the Milan group. His training as a neurologist and a neuroscientist was completed by successive stages passed at the Centre du Langage of La Salpetrière in Paris, under the direction of Professor François Lhermitte, where he studied the phonemic and semantic components of jargon aphasia, and at the department of neurology of the Boston University School of Medicine, where he cooperated with Deepak A. Pandya in tracing the callosal projections from the parietal lobe in the monkey. He pursued the study of aphasia and participated in the construction and validation of the Token Test. His work with François Boller contributed remarkably to convincing people that the test was sensitive to minor deficits of verbal comprehension, since it was able to reveal them even in left-braindamaged patients with no apparent language disorders, that is, those who had passed Pierre Marie’s “three pieces of paper” test, considered in the literature as a demanding comprehension task. Their performance on the Token Test was significantly poorer than that of control patients and right-braindamaged patients (who did not differ between them). This paper was remarkable, not only for its findings, but also for its rigorous methodology and the elegance of its design, features that were to characterize all of Vignolo’s subsequent papers, and that were somewhat uncommon in the neuropsychological literature of that time. These assets were well exemplified by two studies in which Vignolo addressed a thorny question that had been long debated without definite evidence, the efficacy of language rehabilitation. Though practised in several centres and requiring a large amount of effort and money, its efficacy had never been put to a rigorous test due to the many factors involved and the difficulty of their assessment. Taking advantage of the booming activity of the rehabilitation centre set up by Anna Basso within the neurological department of Milan University, Vignolo carried out a preliminary study in which 42 patients, who had undergone a minimum of 20 rehabilitation sessions, were compared before and after treatment with 27 non-rehabilitated patients on a comprehensive aphasia test. The groups were matched for aetiology (mainly vascular), age, time elapsed from the disease onset, and type of aphasia. The percentage of patients who were found to be improved at the second examination was greater in the treated (71%) than in the untreated group (52%), a difference that was encouraging, albeit not significant, and warranted a replication with a larger number of patients and a longer period of treatment. This second study was carried out with Basso, Capitani, and Faglioni in 1975 and involved 91 patients in the treated group (three therapy sessions a week for at least 6 months) and 94 patients in the control group. The number of improved patients was significantly greater in the rehabilitated group, and the efficacy of the treatment was inversely proportional to the length of aphasia; that is, the sooner it was initiated, the better the results. Several questions remained to be addressed, and some of them still wait a definite answer, such as whether the improvement shown by the rehabilitated group is

Dedication to a pioneer in neuropsychology

11

specifically linked to the type of treatment used or reflects the benefits of a generic stimulation. Yet, this was the first time that the result of therapists’ efforts to teach patients how to circumvent the disruption of language skills was confirmed by a scientific study. The late 1950s and the early 1960s witnessed an upsurge of research on hemispheric specialization, which was found not to be confined to the left brain and to involve a wider range of abilities than was formerly thought. In the wake of these studies, Vignolo, working with Faglioni and Spinnler, made an original contribution to specifying the role played by each hemisphere in stimulus recognition, with the right side leading when the task demands perceptual discrimination and the left when it requires the attribution of a meaning or the conceptual categorization of the stimulus. Comparing the performance of right- and left-brain-damaged patients on two tests given in the auditory modality, they brought out a typical instance of double dissociation, the phenomenon thought by Teuber to represent a mainstay of clinical neuropsychology. That is, when two groups are given two tests, group 1 passes test A and fails test B, while group 2 shows the opposite pattern of performance. The two tasks used in this research were the same-different judgement of two meaningless sounds, delivered in succession, and the matching of a meaningful sound with the figure representing its source. The same association of perceptual deficit with right brain damage and of meaning identification with left brain damage was found by other members of the Milan group in the visual modality, and a few years later it was replicated by Vignolo, Cappa, and others in the tactile modality. An issue that remains to be resolved is the extent to which the impairment shown by left hemisphere patients in operations involving conceptual manipulation is contingent upon the loss of the language code or is independent of it. Hemispheric specialization of function in the auditory modality was the subject of further investigation, first in a review paper on auditory agnosia and, more recently, in an experimental study assessing the performance of patients with lesion restricted to either hemisphere on tests requiring the recognition of environmental sounds and certain dimensions of musical sounds (melody and rhythm). The differential contribution of the two halves of the brain to the processing of this kind of stimuli was confirmed: melody was impaired by right brain damage and rhythm by left brain damage, whereas on the environmental sound test, errors were predominantly acoustic in the former group and semantic in the latter. Another area in which Vignolo’s contribution is remarkable is apraxia. Relying on standardized tests and quantitative scores, he succeeded in demonstrating that ideomotor apraxia and apraxia of use are independent disorders affecting the limb gestures, and that apraxia of limb movements dissociates from apraxia of oral movements, the latter being frequently associated with the phonemic-articulatory disorders of Broca’s aphasia. In the 1970s, the introduction in clinical practice of the CT scan began a new chapter in the investigation of the anatomical correlates of neurological

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syndromes. Vignolo was ready to take advantage of this technological breakthrough to address the old, but never exhaustively answered question of language function localization. The traditional approach, based on necroscopy findings, was of unparalleled value in identifying the extent and severity of damage, but suffered from the severe limitation that data were only available in a small minority of patients—those who had died and for whom there was permission to carry out the autopsy—and that they were often obtained at some distance from the behavioural assessment. Although the CT scan is not comparable with necroscopy in terms of sensitivity and accuracy, it represents a remarkable advance in fulfilling the neuropsychologist’s dream of localizing brain damage by non-invasive procedures, suited to be administered to practically every patient. In a series of 90 vascular patients affected by aphasia, Vignolo classified language disorders according to the traditional syndromes and compared them with the locus and extent of damage, as mapped from the CT scan. By and large, there was good agreement between the CT scan and the locus of lesion predicted by the classical theory, as far as the syndromes of fluent aphasia (Wernicke’s and amnestic aphasia) and nonfluent aphasia (Broca’s and transcortical motor aphasia) were concerned. The same held for alexia, agraphia, and pure verbal deafness. On the contrary, some disagreement emerged for global aphasia, which can also follow damage confined to the anterior areas, and for conduction aphasia, which is not necessarily contingent upon the lesion to the arcuate fasciculus. A new finding, which had never been brought out by the traditional clinicoautoptical approach, was the association of aphasia with thalamic haemorrhage. The same methodology was applied to the study of the relation of oral apraxia to language disorders and the definition of its neuroanatomical correlates. More recently, Vignolo has addressed some of the questions raised by the occurrence in right-handed patients of aphasia following a lesion of the right hemisphere, a rare, but long-known exception to the rule of left hemisphere dominance for language, which has been labelled crossed aphasia. In cooperation with a group of Belgian neuropsychologists, he carried out a meticulous revision of the recent literature and identified those patients who had been adequately investigated. To them, nine personal cases were added. The main contribution of the study is the definition of the requirements that must be met to ground the diagnosis of crossed aphasia on a firm basis and the clarification of the hemispheric deficit patterns associated with right brain dominance for language in dextrals. In 1974, Vignolo became associate professor of neurology at the Milan Faculty of Medicine, and in 1982 he was appointed chief of the department of neurology of the Faculty of Medicine of Brescia. Here he assumed the chair as professor of neurology in 1984 and became head of a flourishing group of young investigators, among them J. Abutalebi, S. F. Cappa, F. Mattioli, A. Miozzo, and A. Padovani, who first collaborated with him and then developed their own lines of research, gaining independent reputation. Professor

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Vignolo has come to the end of his academic career. People who have had the privilege to work with him share a feeling of gratitude for the opportunity they had to enjoy the acumen of his mind, the breadth of his knowledge, and, last but not least, the wisdom of his appraisal of men and facts and the keen sense of humour with which he comments on them.

SECTION I

Approaching the brain

1

A multiplicity of intelligences1 Howard Gardner

As a psychologist, I was surprised by the huge public interest in The Bell Curve, the book on human intelligence by psychologist Richard Herrnstein and policy analyst Charles Murray (1994). Most of the ideas in the book were familiar to both social scientists and the general public. Indeed, the Berkeley educational psychologists Arthur Jensen (1969) and Richard Herrnstein (1973) had written popularly about the very same ideas a quarter of a century before. Perhaps, I reasoned, every quarter century a new generation of Americans—and perhaps individuals from other lands—desires to be acquainted with the psychologist’s orthodoxy about intelligence. Thanks to the energies and convictions of a few researchers, the major precepts of “intelligence theory” had been put forth by the second decade of the twentieth century. According to this orthodoxy, there is a single intelligence, often called g for general intelligence. Individuals are born with a certain intelligence or potential intelligence, this intelligence is difficult to change, and psychologists can assess one’s intelligence (or IQ) by short-answer tests and, perhaps, other “purer” measures, such as the time it takes to react to a flashing light or the presence of a certain pattern of brain waves. Soon after this “hedgehog” orthodoxy had been proposed, more “foxlike” critics arose. From outside psychology, commentators like Walter Lippmann (1976) challenged the kinds of items used to assess intelligence, contending that intelligence is more complex and less fixed than the psychometricians had proposed. From within psychology, scientists questioned the notion of a single, overarching intelligence. According to their analyses, intelligence is better thought of as a set of several factors. According to the University of Chicago’s L. L. Thurstone (1938), it makes more sense to think of seven largely independent “vectors of the mind”. The University of Southern California’s J. P. Guilford (1967) enunciated 120 factors, later inflated to 150. The Scottish investigator Godfrey Thomson (1939) spoke about a large number of loosely coupled faculties. And in our own day, Yale’s Robert Sternberg (1985) has proposed a triarchic theory of intellect: these arches encompass a component that deals with standard computational skill, a component that is sensitive to contextual factors, and a component that deals with novelty. Somewhat surprisingly, all of these commentators—whether in favor of or

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opposed to the notion of single intelligence—share one feature: they all believe that the nature of intelligence will be determined by the devising of tests and the analysis of data thus secured. Perhaps, reason monists such as Herrnstein and Murray, performance on a variety of tests will yield a strong general factor of intelligence. And indeed, there is evidence for such a “positive manifold” across tests. Perhaps, counter the pluralists such as Thurstone and Sternberg, the right set of tests will demonstrate that the mind consists of a number of relatively independent factors, with strength in one area failing to predict strength or weakness in other areas. But who says that intelligence needs to be determined on the basis of tests? Were we incapable of making judgments about intellect before Alfred Binet and Francis Galton cobbled together the first set of psychometric items a century ago? If the dozens of IQ tests used around the world were suddenly to disappear, would we no longer be able to make assessments of intellect? Twenty-five years ago, posing just these questions, I embarked on a distinctly different path toward the investigation of intellect. I had been conducting research with two groups: children who were talented in one or more art form and adults who had suffered from a stroke that compromised certain capacities while sparing others. Every day I saw individuals with scattered profiles of strengths and weaknesses, and I was impressed by the fact that a strength or a deficit could cohabit comfortably with different profiles of abilities and disabilities across the variety of humankind. It seemed to me that the data of neurospsychology are a powerful critique of the notion that there exists but a single intelligence. On the basis of such data, I arrived at a firm intuition: human beings are better thought of as possessing a number of relatively independent faculties, rather than as having a certain amount of intellectual horsepower (or IQ) that can be simply channeled in one or another direction. I decided to search for a better formulation of human intelligence. I proposed a new definition: intelligence is a psychobiological potential to process information so as to solve problems or to fashion products that are valued in at least one cultural context. In my focus on fashioning products and my sensitivity to cultural values, I departed from orthodox psychometric approaches such as that adopted by Herrnstein, Murray, and their predecessors. To proceed from an intuition to a definition to a set of human intelligences, I developed a set of criteria. These criteria were drawn from several sources: • • •

psychology: the existence of a distinct developmental history for a capacity; the existence of correlations (or lack of correlations) between certain capacities observations of unusual human beings: individuals who were prodigies, who were idiot savants, or who exhibited learning disabilities anthropology: ethnographic records of how different abilities are developed, ignored, or prized in different cultures

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cultural studies: the existence of symbol systems that encode certain kinds of meanings the biological sciences: evidence that a capacity is represented in particular neural structures; evidence of a distinct evolutionary history for a particular capacity.

Armed with these criteria, I considered many capacities, ranging from those based upon the senses to those involving planning to such possibilities as sense of humor or sexual prowess. To the extent that a candidate’s ability met all or most of the criteria handily, it gained plausibility as intelligence. In 1983, I concluded that seven candidate intelligences met the criteria sufficiently well: linguistic, logical-mathematical, musical, spatial, bodily-kinesthetic, interpersonal, and intrapersonal (Gardner, 1983). Most standard measures of intelligence primarily probe linguistic and logical intelligence, some survey spatial intelligence, and the remaining four are almost entirely ignored. In 1995, invoking new data that fit the criteria, I added an eighth intelligence, that of the naturalist: I am also considering the possibility of a ninth or existential intelligence—one that captures the human proclivity to raise and ponder fundamental questions about existence, life, death, finitude (see Gardner 1999a, Chapters 4 and 5). Whether existential intelligence gets to join the inner sanctum depends on whether convincing evidence accrues about the distinct neural basis of such intelligence. The theory of multiple intelligences (MI theory, as it has come to be called) makes two strong claims. The first claim is that all human beings possess all of these intelligences: indeed, they can be considered a definition of Homo sapiens, cognitively speaking. The second claim is that, just as we all look different and have different personalities and temperaments, we also exhibit different profiles of intelligences. No two individuals, not even identical twins or clones, have exactly the same amalgam of intelligences, foregrounding the same strengths and weaknesses. This is because, even in the case of identical genetic heritage, individuals undergo different experiences and also seek to distinguish their profiles from one another. Within psychology, MI theory has generated controversy. Many researchers are nervous about the movement away from standard tests, and the adoption of a set of criteria that are unfamiliar and less susceptible to quantification. Herrnstein and Murray (1994) called it a “radical theory”. Some have questioned whether the theory is empirical. However, this criticism misses the mark. MI theory is based completely on empirical evidence. The number of intelligences, their delineation, and their subcomponents are all subject to alteration in the light of new findings. Indeed, the naturalist intelligence could be asserted only after evidence had accrued that parts of the temporal lobe are dedicated to the naming and recognition of natural kinds, as opposed to manmade “artificial” objects (Damasio & Damasio, 1995; Warrington & Shallice, 1984). Much of the evidence for the personal intelligences has come from research in recent decades on emotional intelligence (Goleman, 1995) and on

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the development in children of a “theory of mind” (Astington, 1993). The intriguing finding that musical experiences may enhance spatial capacities raises the possibility that musical and spatial intelligences may draw on certain common abilities, such as the capacity to handle complex architectonic structures (Rauscher, Shaw, & Ky, 1993). It is also worth noting that the movement toward multiple intelligences is quite consistent with trends in related sciences. Neuroscience recognizes the modular nature of the brain, evolutionary psychology is based on the notion that different capacities have evolved in specific environments for specific purposes, and artificial intelligence increasingly embraces expert systems rather than general problem-solving mechanisms. Indeed, within science, the believers in a single IQ or general intelligence are increasingly isolated, their positions more likely to be embraced by those, like Herrnstein and Murray (1994), who have an ideological ax to grind. If psychologists express skepticism about MI theory, educators around the world have embraced the idea. MI theory not only comports with their intuitions that children are smart in different kinds of ways but also holds out the hope that more students can be reached more effectively, if their favored ways of knowing are taken into account in curriculum, instruction, and assessment. In many parts of the world, a virtual cottage industry has risen to create MI schools, classrooms, curricula, texts, computer systems, and the like. Most of this work is well intentioned, and some of it has proved quite effective in motivating students and in giving them a sense of involvement in intellectual life. However, various misconceptions have risen: for example, that every topic should be taught in seven or eight ways, or that the purpose of school is to identify (and broadcast) students’ intelligences, possibly by administering an octet of new standardized tests. I have begun to speak out about some of these less advisable beliefs and practices (Gardner, 1999a). MI theory is best thought of as a tool, rather than as an educational goal. Educators need to determine, in conjunction with their communities, the goals that they are seeking. Once these goals have been articulated, MI theory can provide powerful support. In my view, schools should seek to develop individuals of a certain sort—civic-minded, sensitive to the arts, and deeply rooted in the disciplines. Schools should probe pivotal topics with sufficient depth so that students end up with a comprehensive understanding of these topics. Approaches founded on MI theory have demonstrated considerable promise in helping schools to achieve these goals (Kornhaber, Fierros, & Veenema, 2003). Experts interested in intelligence have debated certain topics for nearly a century: is there one intelligence or more than one? Can intelligence(s) be altered? Is intelligence inborn or acquired? It would take a brave seer to predict that these debates will disappear. (In fact, if I am correct, a latter-day Herrnstein or Murray will author her own variation on The Bell Curve around 2020.) As the person most closely associated with MI theory, I record three wishes for this line of work.

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A broader but not infinitely expanded view of intelligence It is time that intelligence is broadened to include a range of human computational capacities, including those that deal with music, other persons, and skills in deciphering the natural world. However, it is important that intelligence should not be conflated with other virtues, such as creativity, wisdom, or morality. I also contend that intelligence should not be so broadened that it crosses the line from description to prescription. I endorse the notion of emotional intelligence when it denotes the capacity to compute information about one’s own or others’ emotional life. However, when the term comes to encompass the kinds of persons we hope to develop, we have crossed the line into a value system—and that should not be part of our conception of intelligence. Thus, when Daniel Goleman stresses the importance of empathy as part of emotional intelligence, I go along with him. But Goleman also urges that individuals care for one another, thus crossing an important boundary. The possession of the capacity to feel another’s suffering is not the same as the decision to come to her aid. Indeed, a sadistic individual might use her knowledge of another’s psyche to inflict pain.

A shift away from standardized, short-answer, “proxy” instruments to real-life demonstrations or virtual simulations During a certain historical period, it may have been necessary to assess individuals by administering items that are themselves of little interest (such as repeating numbers backward) but are thought to correlate with skills or habits of importance. Nowadays, however, given the advent of computers and virtual technologies, it is possible to look directly at individuals’ performances, to see how they can argue, debate, look at data, critique experiments, execute works of art, and so on. As much as possible, we should train students directly in these valued activities and we should assess how they carry out valued performances under realistic conditions. The need for ersatz instruments, whose relation to real-world performance is often tenuous at best, should wane.

The use of multiple intelligences ideas for more effective pedagogy and assessment I have little sympathy for educational efforts that seek simply to “train” the intelligences or to use the intelligences in trivial ways (such as singing multiplication tables or playing Bach while one is doing geometry). For me, the educational power of multiple intelligences is exhibited when these faculties are drawn on to help students master consequential disciplinary materials. In The Disciplined Mind (1999b), I focus on three rich topics: the theory of evolution (as an example of scientific truth), the music of Mozart (as an

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example of artistic beauty), and the Holocaust (as an example of immorality in recent history). In each case, I show how the topic can be introduced to students through a variety of entry points (drawing respectively on several intelligences), how the subject can be made more familiar through the use of analogies and metaphors drawn from diverse domains, and how the core ideas of the topic can be captured through not a single symbolic language but rather a number of complementary model languages or representations. By this approach, the individual who understands evolutionary theory can think in terms of a historical narrative, a logical syllogism, a quantitative examination of evolving populations in different niches, a diagram of species delineation, a dramatic sense of the struggle among individuals (or genes or populations), and so on. The individual who can think of evolution in only one way—using only one model language—actually has a tenuous command of the principal ideas. The issue of who owns intelligence has been an important one in our society for some time, and it promises to be a crucial and controversial one for the foreseeable future. For too long, society has been content to leave intelligence in the hands of psychometricians. Often these test makers have a narrow, overly scholastic view of intellect; they rely on a set of instruments that are destined to valorize certain capacities, while ignoring those that do not lend themselves to ready formulation and testing. And in the hands of those with a political ax to grind, they often skate close to the dangerous territory of eugenics. MI theory represents at once an effort to base the conception of intelligence on a much broader scientific basis, to offer a set of tools to educators that will allow more individuals to master substantive materials in an effective way, and to help each individual achieve his or her human potential at the workplace, in avocations, and in the service of the wider world.

Note 1 An earlier version of this chapter was published in Scientific American (1998).

References Astington, J. (1993). The child’s discovery of the mind. Cambridge, MA: Harvard University Press. Damasio, A., & Damasio, H. (1955). Recent trends in cognitive neuroscience. Lecture presented at the Center for Advanced Study in the Behavioral Sciences, Stanford, California. Gardner, H. (1983). Frames of mind: The theory of multiple intelligences. New York: Basic Books. Gardner, H. (1999a). Intelligence reframed: Multiple intelligences for the 21st century. New York: Basic Books. Gardner, H. (1999b). The disciplined mind. New York: Simon and Schuster. Goleman, D. (1995). Emotional intelligence. New York: Bantam Books. Guilford, J. P. (1967). The nature of human intelligence. New York: McGraw-Hill.

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Herrnstein, R. (1973). IQ in the meritocracy. Boston: Little, Brown. Herrnstein, R., & Murray, C. (1994). The bell curve. New York: Free Press. Jensen, A. (1969). How much can we boost IQ and scholastic achievement? Harvard Educational Review, 39, 1–123. Kornhaber, M., Fierros, E., & Veenema, S. (2003). Multiple intelligences: Best ideas from research and practice. Boston: Allyn and Bacon. Lippmann, W. (1976, trans. 1922–3). Readings from the Lippmann–Terman debate. In N. J. Block & G. Dworkin (Eds.), The IQ controversy: Critical readings. New York: Pantheon. Rauscher, F., Shaw, G. L., & Ky, K. N. (1993). Music and spatial task performance. Nature, 365, 611. Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. New York: Cambridge University Press. Thomson, G. (1939). The factorial analysis of human ability. Boston: Houghton Mifflin. Thurstone, L. L. (1938). Primary mental abilities. Chicago: University of Chicago Press. Warrington, E., & Shallice, T. (1984). Category-specific semantic impairments. Brain, 107, 829–854.

2

Neural circuitry underlying language Michael Petrides and Deepak N. Pandya

The neural processing underlying language, one of the higher cognitive achievements of the human brain, is mainly dependent on the cerebral cortex. Many cortical regions contribute to language, and specific association pathways that interconnect these cortical regions permit functional interactions underlying various forms of linguistic processing. Current understanding of the cerebral cortical structures and the association fiber pathways that are involved in language are based on the pioneer investigations of scientists, such as Broca (1861), Wernicke (1874), Lichtheim (1885), and Dejerine (1914). In the 1960s, Geschwind presented his ideas on the higher cortical functions and, in particular, language in an influential series of papers on disconnection syndromes (Geschwind, 1965, 1970, 1974). This work, which synthesized the classical views on the anatomy of language in a modern form, has had a tremendous influence on current conceptions of the anatomical organization of language. Geschwind’s ideas were largely based on older anatomical observations obtained in the human brain in the latter part of the nineteenth century and the early part of the twentieth century, as well as on physiological, neuronographic studies carried out on nonhuman primates from the 1940s and 1950s (e.g. Bailey, Bonin, Davis, Garol, & McCulloch, 1944; Bailey, Bonin, Garol, & McCulloch, 1943; Dusser de Barrene, Garol, & McCulloch, 1941; French, Sugar, & Chusid, 1948; Pribram & MacLean, 1953; Sugar, French, & Chusid, 1948; Ward, Peden, & Sugar, 1946). In the latter part of the twentieth century and more recently, major advances have been made in experimental neuroanatomical methods, permitting a precise understanding of the origins, trajectories, and terminations of the association fiber pathways of the nonhuman primate brain. Although the information provided by experimental anatomical methods is based largely on studies of the macaque monkey brain, it provides important insights on the general organization of the primate cortical connections with major implications for our understanding of human cortical functions, including language (Petrides and Pandya, 2002a). Modern studies with diffusion tensor imaging promise to provide important information regarding the association fiber pathways of the human brain, but this work, which is still in an early stage of development, can, at present, demonstrate only the major parts of fiber pathways without

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detailed information on their precise origins and terminations within particular cortical architectonic areas (e.g. Campbell, Siddiqi, Rymar, Sadikot, & Pike, 2005; Catani, Jones, & ffytche, 2005; Croxson et al., 2005; JohansenBerg et al., 2004; Makris et al., 2005, in press; Mori & van Zijl, 2002). In this chapter, we shall describe the association pathways that are considered to be involved in language processing, both from the classical perspective and from insights provided by modern neuroanatomical studies on the macaque monkey.

Core language pathways The currently dominant conception of the anatomy of language, which is based on the classical studies and has been crystallized in the writings of Geschwind, postulates a predominantly receptive language-processing region (Wernicke’s area) in the posterior temporal lobe of the left hemisphere and an anterior language region (Broca’s area), located in the posterior part of the inferior frontal gyrus, that is thought to be primarily involved in the expressive aspects of speech (Figure 2.1). These two major language regions are thought to be connected via the arcuate fasciculus (AF), which permits functional interactions between the receptive region in the temporal lobe and the expressive region in the inferior frontal gyrus (Geschwind, 1965, 1970, 1974). Although it is widely held that the arcuate fasciculus is the main association fiber pathway enabling these interactions, the anatomical evidence on which this view is based is fraught with difficulties (e.g. Petrides & Pandya, 2002a, 2006). In the older literature, the terms “arcuate fasciculus” and “superior longitudinal fasciculus” were used interchangeably (e.g.

Figure 2.1 Schematic drawing of the lateral surface of the left hemisphere of the human brain showing the arcuate fasciculus (A), which is presumed to connect Broca’s area (B) with Wernicke’s area (W). Based on Geschwind (1974).

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Dejerine, 1895). These pathways were first demonstrated by the then available method of gross dissection, and toward the end of the nineteenth century, various attempts were made to elucidate the origin, trajectory, and termination of these association pathways by histological staining methods, such as the myelin stain of Pal and Weigert (Dejerine, 1895). Despite these efforts, the precise origin and termination of these fiber systems remained uncertain. Dejerine (1895, p. 758) reviewed the knowledge available at that time and concluded that the arcuate/superior longitudinal fasciculus did not consist of long association fibers connecting distant cortical regions, but rather of short association fibers joining adjacent convolutions. Later, the term “arcuate fasciculus” was restricted to the fibers derived from the temporal lobe, which arch (hence the term “arcuate”) around the caudal part of the Sylvian fissure on their way to the frontal lobe. The term “superior longitudinal fasciculus” was restricted to the fibers derived from the parietal lobe and directed to the frontal lobe in a more or less horizontal course in the white matter above the Sylvian fissure. Thus, the arching fibers originating from the caudal superior temporal lobe, namely the arcuate fasciculus, and those from the parietal region, namely the superior longitudinal fasciculus, were considered to run a common course above the Sylvian fissure toward the frontal lobe. Since the 1960s, the experimental anterograde tract-tracing methods that were developed, initially the silver-staining method (e.g. Nauta, 1957) and later the autoradiographic method (Cowan et al., 1972), permitted extensive investigations of the cortico-cortical association pathways in the nonhuman primate brain (Petrides & Pandya, 2002a). Although linguistic processing does not exist in the macaque monkey brain, our comparative architectonic studies of the human and the macaque monkey frontal cortex show a comparable architectonic organization, including precursor zones in the nonhuman primate brain to the language areas found in the human brain (Petrides, Cadoret, & Mackey, 2005; Petrides & Pandya, 1994) (Figure 2.2). Comparable observations regarding the existence of equivalent auditory-related areas in the temporal lobe of the monkey and the human brain have been recently made by Hackett, Pruess, and Kaas (2001) and Fullerton and Pandya (2007). Using the autoradiographic, tract-tracing method, which allows excellent visualization of the origin, trajectory, and termination of fiber pathways, we have studied, in the rhesus monkey, the connections originating from the parietal and temporal cortical areas and terminating in the frontal cortex, as well as the reciprocal connections originating in the frontal cortex and directed back to the parietal and temporal areas (Petrides & Pandya, 1984, 1988, 2006, 2007). These studies have demonstrated that there are three distinct, long association pathways that emanate from the superior temporal gyrus and the adjacent cortex of the upper bank of the superior temporal sulcus and lead to the frontal lobe (Petrides & Pandya, 1988). The most caudal part of the superior temporal gyrus (area Tpt) (Figure 2.3) and the adjacent region of the superior temporal sulcus give rise to a pathway that arches around the caudal part of the Sylvian fissure

Figure 2.2 Architectonic subdivisions of the lateral surface of the human (A) and the macaque monkey (B) prefrontal cortex (Petrides and Pandya, 1994).

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Figure 2.3 Composite diagram to show the location of the architectonic areas on the medial, lateral, and ventral views of the monkey cortex.

and progresses forward in the white matter above the Sylvian fissure, eventually moving dorsally to terminate in the rostro-dorsal part of area 8 (area 8Ad) of the frontal cortex. This pathway can, therefore, be considered as the arcuate fasciculus, because its fibers arch around the caudal end of the Sylvian fissure as they are directed toward the frontal lobe (Figure 2.4). The middle part of the superior temporal gyrus (areas PaAlt, TS3, and TS2) and the adjacent part of the superior temporal sulcus (TAa and TPO) give

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Figure 2.4 Schematic diagram to illustrate the origin, course, and termination of the arcuate fasciculus (AF) (Petrides & Pandya, 1984).

rise to association fibers that travel via the extreme capsule and terminate in ventrolateral area 45 and the dorsal prefrontal areas 9 and 46, as well as area 10 (Figure 2.5). From the rostral-most part of the superior temporal gyrus (areas TS1 and TS2) and the dorsal part of temporal polar proisocortex (Pro), association fibers course via the uncinate fasciculus and terminate in

Figure 2.5 Schematic diagram to illustrate the origin, course, and terminations of the extreme capsule fiber system (EC) (Petrides & Pandya, 1988).

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area 47/12, as well as in area 13, the proisocortex of the orbital frontal cortex, and the medial prefrontal areas 25, 14, and 32 (Figure 2.6). As pointed out above, the classical view has been that the arcuate fasciculus is the main language pathway connecting Wernicke’s area in the posterior temporal region with Broca’s area in the inferior frontal cortex. However, the experimental anatomical studies in the monkey show that the temporofrontal fibers that arch around the Sylvian fissure, and which therefore form the arcuate (i.e. arching) fasciculus, connect the caudal part of the superior temporal gyrus with the dorsal part of area 8. This region of the frontal lobe is involved in spatial attentional processing and is not a precursor of Broca’s area, which is found in the caudal ventrolateral prefrontal cortex (Petrides et al., 2005). The fibers which are directed toward the ventrolateral prefrontal cortex originate from the middle to posterior part of the superior temporal gyrus and adjacent superior temporal sulcus, course via the extreme capsule, and terminate in prefrontal areas, including area 45 (Petrides & Pandya, 2002a). It should be noted that these connections are bidirectional (Petrides & Pandya, 2006, 2007). Area 45 in the human brain occupies the pars triangularis of the inferior frontal gyrus and, in the left hemisphere, is part of the anterior language region (e.g. Amunts, Schleicher, Ditterich, & Zilles, 2004; Amunts et al., 1999; Petrides, 2006). Experimental anatomical studies of the association pathways in the monkey brain showed that the fibers originating from the parietal cortex, and which are directed to the frontal cortex, course via the superior longitudinal fasciculus (Petrides & Pandya, 1984). We demonstrated that the superior

Figure 2.6 Schematic diagram to illustrate the origin, course, and terminations of the uncinate fasciculus (UF) (Petrides & Pandya, 1988).

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longitudinal fasciculus (SLF) is a complex fiber system consisting of three separate components. SLF I fibers stem from the medial and dorsal parts of the parietal lobe (areas PE, PEc, and PGm) and course through the dorsal white matter of the parietal and frontal lobe leading to the supplementary motor area (MII) and dorsal areas 6 and 8 (Figure 2.7) (Petrides & Pandya, 1984). SLF II fibers originate from the caudal part of the inferior parietal lobule (areas PG and Opt) and the lower bank of the intraparietal sulcus (area POa) and travel in the white matter above the Sylvian fissure to terminate in the dorsal parts of areas 6 and 8 and in areas 46 and 9/46 (Figure 2.8). In contrast, SLF III fibers originate from the rostral part of the inferior parietal lobule (area PF) and the adjacent part of the intraparietal sulcus (rostral area POa, also known as AIP), and course through the white matter of the dorsal Sylvian operculum to terminate in the ventral part of area 6 and adjacent area 44, area ProM, as well as in the ventral part of area 9/46 (Figure 2.9). Thus, area 44, which in the human brain is the part of Broca’s area occupying the pars opercularis of the inferior frontal gyrus, is connected via SLF III with the rostral inferior parietal cortex, a region equivalent to the supramarginal gyrus (Economo’s area PF or Brodmann’s area 40) of the human brain. These observations in terms of connectional origins and terminations have been supported by a number of other studies in recent years using retrograde tracer techniques (Cavada & Goldman-Rakic, 1989; Deacon, 1992; Hackett, Stepniewska, & Kaas, 1999; Petrides & Pandya, 1999, 2002b; Romanski, Bates, & Goldman-Rakic, 1999). In addition, in a recent study using diffusion tensor imaging, the stem portion of these three distinct components of the

Figure 2.7 Schematic diagram to illustrate the origin, course, and terminations of the dorsal component of the superior longitudinal fasciculus (SLF I) (Petrides & Pandya, 1984).

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Figure 2.8 Schematic diagram to illustrate the origin, course, and terminations of the middle component of the superior longitudinal fasciculus (SLF II) (Petrides & Pandya, 1984).

superior longitudinal fasciculus have been demonstrated in the human brain in vivo (Makris et al., 2005). When the above-mentioned findings from experimental anatomical studies in the monkey are extrapolated to the human brain, they suggest that there

Figure 2.9 Schematic diagram to illustrate the origin, course, and terminations of the ventral component of the superior longitudinal fasciculus (SLF III) (Petrides & Pandya, 1984).

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are two distinct association pathways that are involved in language functions. One such pathway consists of fibers originating from cortex on the middle to posterior part of the superior temporal gyrus and the adjacent superior temporal sulcus, running through the extreme capsule, and terminating in area 45. The other pathway, namely SLF III, originates in the rostral part of the inferior parietal lobule and connects preferentially with area 44. It should be pointed out that, according to our recent studies, both these pathways are bidirectional in nature (Petrides & Pandya, 2006). Thus, it appears that the notion of a single language pathway, namely the arcuate fasciculus, connecting a posterior temporal language region (Wernicke’s area) with Broca’s region in the inferior frontal gyrus needs to be revised. The currently available experimental anatomical material suggests instead the following scheme: the two distinct architectonic entities that constitute Broca’s region, namely the dysgranular area 44 and the granular area 45, have different connection patterns with posterior cortical regions. These differences in connectivity can provide important clues with regard to the cortical networks in which these two areas are embedded and therefore to their fundamental function. Area 44 is bidirectionally linked with the rostral part of the inferior parietal lobule (area PF) (Figure 2.9), which, in the human brain, occupies the supramarginal gyrus. The rostral part of the inferior parietal lobule is a multimodal cortical region with emphasis on action processing, as shown by the fact that neurons in this area of the monkey brain exhibit complex bodycentered responses (e.g. Hyvarinen & Shelepin, 1979; Leinonen, Hyvarinen, Nyman, & Linnankoski, 1979; Robinson & Burton, 1980; Taira, Mine, Georgopoulos, Murata, & Tanaka, 1990). The local connections of area 44 within the frontal lobe also suggest that it is a primarily somatomotor structure. Area 44 is connected with the rostral part of the ventral premotor cortex (area F5), which has both orofacial (most ventrally) and hand/arm representations (more dorsally) and is, in turn, connected with the parts of the primary motor cortex (area 4) that control the orofacial and the arm/hand musculature. Area 44 is also connected with motor areas on the medial part of the hemisphere, such as the supplementary and cingulate motor cortical areas (Petrides and Pandya, 2004). This connection pattern of area 44 suggests that it may be at a privileged position for the high-level control of motor behavior and, by extension, the expression of communicative behavior. The fact that architectonic area 44 can be identified in the ventrolateral frontal cortex of the macaque monkey suggests that the contribution of this area to the expressive aspects of communicative behavior may have preceded the evolution of linguistic ability in the human brain and may reflect a general function of area 44 (Petrides and Pandya 1994; Petrides et al., 2005). With the evolution of linguistic ability in the human brain, area 44 is, therefore, an ideal structure to serve certain aspects of speech production. Kimura (1993) has reviewed the large body of evidence suggesting a strong link between communicative function in the human left hemisphere and its capacity for complex motor control.

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In sharp contrast to area 44, which is linked to the inferior parietal lobule via SLF III, area 45 is bidirectionally linked to the middle part of the superior temporal gyrus and the adjacent superior temporal sulcus via fibers that course in the extreme capsule (Figure 2.5) (Petrides & Pandya, 1988). The middle part of the superior temporal gyrus is a primarily auditory association cortical region (Kaas & Hackett, 2002; Pandya & Sanides, 1973; Wallace, Johnston, & Palmer, 2002), and the adjacent superior temporal sulcus is thought to be a polysensory cortical region based on anatomical (Seltzer & Pandya, 1978, 1994), lesion/behavioral (Petrides & Iversen, 1978), and neuron-recording studies (Baylis, Rolls, & Leonard, 1987; Benevento, Fallon, Davis, & Rezak, 1977; Bruce, Desimone, & Gross, 1981; Desimone & Gross, 1979; Hikosaka, Iwai, Saito, & Tanaka, 1988). Petrides has argued that the midportion of the ventrolateral prefrontal cortex (areas 45 and 47/12) is critical for the active (i.e. controlled strategic) regulation of information in the posterior cortical association areas where information is perceived and coded in short-term and long-term form (Petrides, 1994, 1996). This role of the midventrolateral prefrontal cortex (areas 45 and 47/12) can be contrasted with that of the mid-dorsolateral prefrontal cortex (areas 9, 9/46 and 46), which is involved in the monitoring (tracking) of mnemonic performance on the basis of the subject’s current plans (Petrides, 1994, 1996). These fundamental functional contributions of the mid-dorsolateral (areas 9, 46, 9/46) and the mid-ventrolateral prefrontal regions (areas 45 and 47/12) are true of the nonhuman, as well as the human, primate brain (see Petrides, 1994, 1996, for details). It is likely that, with the evolution of language in the human brain, the more general prelinguistic role of the mid-ventrolateral prefrontal region (areas 45 and 47/12) in the active controlled retrieval of information from posterior cortical areas was adapted for the active retrieval of linguistic information, particularly in the left hemisphere (see Petrides, 2006). In recent years, a large number of data on language processing has been provided by functional neuroimaging studies of the normal human brain. One can therefore ask whether the overall picture emerging from functional neuroimaging research is consistent with the suggestion from monkey experimental anatomical studies that there might be two distinct and separable language circuits involving the two architectonically distinct parts of Broca’s region, namely areas 44 and 45, which interact with different posterior cortical association regions via distinct fiber pathways. The following section will review the available data, which appear to be consistent with the experimental anatomical evidence, and not with the classical view of a single fiber pathway linking anterior and posterior language areas. In an early positron emission tomography study, Paulesu, Frith, and Frackowiak (1993) observed that area 44 shows increased activity during articulatory/phonological processing and, importantly, that it is coactivated with the supramarginal gyrus during such processing. Note that this finding is perfectly consistent with the experimental anatomical studies in the monkey which have shown that the posterior cortical connections of area 44 are with

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the rostral inferior parietal lobule (i.e. the supramarginal gyrus), and not with the caudal part of the superior temporal gyrus, as is often assumed. There is also other functional neuroimaging evidence suggesting that area 44 may be involved in articulatory/phonological processing (e.g. Fiez, Raife, Balota, Schwarz, Raichle, & Petersen, 1996; Poldrack, Wagner, Prull, Desmond, Glover, & Gabrieli, 1999; Price, Moore, Humphreys, & Wise, 1997), consistent with the anatomical evidence showing that area 44 is embedded in a primarily somatomotor network. In contrast to the role of area 44 in articulatory/ phonological processing, there is evidence that the mid-ventrolateral prefrontal area 45 is involved in the active retrieval of verbal information. Active, controlled retrieval is required in situations where information cannot simply be retrieved as a result of automatic recognition or strong contextual associative links (Petrides, 1994, 1996). In this context, it has been shown that activity in the mid-ventrolateral prefrontal cortex (area 45) increases during active verbal retrieval, primarily, in the left hemisphere (Petrides, Alivisatos, & Evans, 1995). Increased activity in the right ventrolateral prefrontal cortex (area 47/12) is observed during active retrieval for nonverbal visual or visuospatial information (Cadoret, Pike, & Petrides, 2001; Kostopoulos & Petrides, 2003; Petrides, Alivisatos, & Frey, 2002). In the positron emission tomography study which tested the prediction that the mid-ventrolateral prefrontal cortex, in the left hemisphere, is involved in the active, strategic retrieval of verbal information from long-term memory, the main experimental condition involved the free recall of a list of arbitrary words that had been studied before scanning (Petrides et al., 1995). Free recall under these conditions is the result of active strategic retrieval processes, since the subject is asked to recall a specific set of arbitrary words that were presented on a particular occasion, namely the particular words studied before scanning. One of the control conditions, a well-learned verbal associate task, was designed to involve automatic verbal retrieval. In comparison with the highly learned, paired-associate task (i.e. automatic retrieval), the free recall task (i.e. active retrieval) revealed significantly greater activity in the left midventrolateral prefrontal cortex (area 45) and at the same time less activity in the middle part of the superior temporal gyrus and adjacent superior temporal sulcus (Figure 2.10). Note that this activation pattern is consistent with the above-mentioned experimental anatomical findings in the monkey showing that area 45 is strongly connected via the extreme capsule with the middle section of the superior temporal gyrus and superior temporal sulcus (Figure 2.5). Another well-known and reliable finding from functional neuroimaging studies is the frequently observed increase in activity within the left ventrolateral prefrontal cortex during the performance of tasks that require semantic retrieval (Buckner, Raichle, & Petersen, 1995; Klein, Milner, Zatorre, Meyer, & Evans, 1995; Petersen, Fox, Posner, Mintun, & Raichle, 1988). The evidence suggests that the mid-ventrolateral prefrontal cortex (areas 47/12 and 45) is involved in the controlled retrieval of semantic information, while the

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Figure 2.10 Three-dimensional reconstruction of the left hemisphere of the human brain showing increased activity in ventrolateral area 45 during verbal episodic active retrieval. Note that activity in the middle part of the superior temporal gyrus and adjacent superior temporal sulcus has decreased. Based upon a positron emission tomography study by Petrides et al. (1995). AS: ascending sulcus; HS: horizontal sulcus; IFS: inferior frontal sulcus; SF: Sylvian fissure; STS: superior temporal sulcus. (This figure is published in color at www.psypress.com/brainscans-etc/)

posterior ventrolateral region (areas 44 and 6) is related to the control of phonological processing (Fiez et al., 1996; Poldrack et al., 1999; Price et al., 1997). One example of semantic retrieval is the verbal fluency task, in which the subject is required to produce words from a certain semantic category (e.g. animals). When activation during the semantic retrieval task (e.g. listing animals) is compared with activation of highly automatic retrieval (e.g. listing the days of the week), greater activity is often observed within the left ventrolateral prefrontal cortex, involving area 45. This finding has recently been confirmed in a functional magnetic resonance imaging study, in which regions of interest within area 44 and area 45 were set up, using cytoarchitectonic, probabilistic maps (Amunts et al., 2004). The increases in activity during semantic retrieval were clearly shown to be focused within area 45, rather than area 44. Thus, by virtue of the distinct connectivity patterns of area 45 and the above functional neuroimaging observations, Petrides (2006) suggested that the temporofrontal extreme capsule fiber system is involved in nonarticulatory aspects of language processing that are necessary for the retrieval of linguistic information, both episodic and semantic lexical. By contrast, the ventral component of the superior longitudinal fasciculus (i.e. SLF III)

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provides a means of functional interaction between area 44 and ventral premotor area 6, which deal with the articulatory/phonological aspects of language, and the rostral inferior parietal lobule (supramarginal gyrus and rostral intraparietal sulcus) (Petrides, 2006).

Pathways involved in metalinguistic processing Language operates in the context of other higher cognitive processes, and it both influences and is influenced by those other cognitive processes. Thus, in addition to the cortical areas and pathways that are directly involved in language processing, other cortical regions and association pathways may contribute to language by subserving aspects of metalinguistic processing. Below, we comment on the possible role of these other pathways. Arcuate fasciculus The experimental anatomical studies in the monkey have shown that the arcuate fasciculus, which was classically thought to be the core language pathway, connects the most caudal part of the superior temporal gyrus with the dorsal part of area 8 (Figure 2.4). In the monkey, the caudal part of the superior temporal gyrus has been shown to play a role in the processing of sound location (Kaas & Hackett, 2002; Leinonen, Hyvarinen, & Sovijarvi, 1980; Romanski et al., 1999; Tian, Reser, Durham, Kustov, & Rauschecker, 2001). There is also evidence from functional neuroimaging that this may be the case in the human brain (Warren, Zielinski, Green, Rauschecker, & Griffiths, 2002; Zatorre, Bouffard, Ahad, & Belin, 2002). Furthermore, the dorsal part of area 8, with which the caudal part of the superior temporal gyrus is connected, has been shown to play a role in the allocation of attention to sound location (Azuma & Suzuki, 1984; Lilly, 1965; Suzuki, 1985; Vaadia, Benson, Hienz, & Goldstein, 1986). These facts suggest the following hypothesis. Information from the primary auditory cortex of the supratemporal plane would reach both the middle part (areas PaAlt, Ts3, and Ts2) and the caudal part (Tpt) of the superior temporal gyrus, as well as the adjacent polysensory parts of the superior temporal sulcus (i.e. area TPO). These areas, in turn, both send and receive information from the frontal cortex via separate pathways. The middle section of the superior temporal gyrus and sulcus would, via the extreme capsule, be primarily engaged in language processing, whereas the most caudal portion of the superior temporal gyrus (area Tpt) might contribute to the direction of attention to the source of sound via the arcuate fasciculus (Figures 2.4 and 2.5). Although the arcuate fasciculus has been demonstrated with diffusion tensor imaging in the human brain (Catani et al., 2005), it is not possible with current methodology to determine with certainty that the axons terminate in Broca’s region. It should also be noted that these axons would mingle with those of SLF II and SLF III in the white matter of the supramarginal gyrus and would be hard to

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separate them so as to establish their respective terminations. Note that SLF III does terminate in area 44 in the macaque monkey. Superior longitudinal fasciculus: SLF I and SLF II In addition to the classical peri-Sylvian language zones, Penfield and his colleagues identified a supplementary speech region on the medial surface of the hemisphere anterior to the primary motor region (Penfield & Roberts, 1959). Electrical stimulation of either hemisphere in the supplementary motor region produces vocalization of meaningless sounds, as well as slowing, hesitation, slurring, or even arrest of speech. Stimulation limited to the left supplementary motor region produces failures to name stimuli or misnaming them because of substitution of synonyms and unrelated words, while speaking per se might not be affected. Despite these observations, the role of the supplementary motor region in language remains obscure. Lesions of the dorsomedial surface of the frontal lobe do not cause long-lasting aphasia. Immediately after such brain damage, mutism or severely reduced and hesitantly initiated speech is observed. During the recovery phase, initiation of spontaneous propositional speech may be severely impaired, but other forms of speech output, such as repetition of heard speech or serial automatic speech (e.g. counting), may be intact. Within months, most patients recover their ability to initiate and sustain conversation (Alexander & Schmitt, 1980; Jonas, 1981; Masdeau, Schoene, & Funkenstein, 1978; Rubens, 1975). There also appears to be no difficulty with the syntactic structure of language after lesions of the supplementary motor region. Thus, the supplementary motor region appears to play a role in the initiation and fluent execution of speech, particularly of propositional speech, perhaps reflecting a general role in motor production in the context of language. Electrocortical activity, referred to as the readiness potential, is often recorded from the frontal midline during the preparation for voluntary motor activity (Deecke & Kornhuber, 1978). It has been shown that this electrical response is related to activity in the supplementary motor cortex and the cingulate motor areas (e.g. Cunnington, Windischberger, Deecke, & Moser, 2003). The supplementary motor region is primarily connected with the superior and medial parietal cortex via SLF I (Figure 2.7) and, perhaps, this somatomotor system may be involved in the initiation of voluntary motor behavior. As pointed out above, the second component of the superior longitudinal fasciculus, namely SLF II, interconnects the caudal part of the inferior parietal lobule (a region equivalent to the angular gyrus in the human brain) with the dorsal frontal areas 6 and 8 and area 9/46 (Figure 2.8). Since the classic cases of Dejerine (1891, 1892, 1914) that demonstrated the syndrome of alexia with agraphia after lesions of the left posterior parietal cortex involving the angular gyrus, it has been traditionally accepted that this region of the cerebral cortex is critical for reading and writing (Geschwind, 1970). SLF II provides critical interactions between the caudal part of the posterior parietal

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Figure 2.11 Three-dimensional reconstruction of the left hemisphere of the human brain showing increased activity in the supramarginal gyrus, the central sensorimotor cortex, and the supplementary motor cortex during writing. Based upon a positron emission tomography study by Petrides et al. (1995). CS: central sulcus; IPS: intraparietal sulcus; SMA: supplementary motor area; SF: Sylvian fissure. (This figure is published in color at www.psypress.com/brainscans-etc/)

region with the premotor cortex (area 6) and the visuospatial prefrontal region (area 8A) that may underlie various aspects of the reading and writing process. The contribution of the inferior parietal lobule to reading and writing processes may reflect the engagement of the spatial information processing that is well known to depend on this region of the cortex in the service of linguistic processing that is critically dependent on spatial analysis (reading) and action in space (writing). Strong activation of the rostral inferior parietal cortex (supramarginal gyrus), the midportion of the central sensorimotor region (i.e. the hand/arm representation), and the supplementary motor cortex has been observed during writing to dictation (Petrides et al., 1995) (Figure 2.11). Activation of the posterior inferior parietal cortex (angular gyrus) during reading has been rather inconsistent in functional neuroimaging studies, but it has been observed during slow reading of unrelated words (Price et al., 1996) and during reading of sentences (Bavelier, Corina, Jezzard, Padmanabhan, Prinster, & Braun, 1997). Middle longitudinal fasciculus The posterior region of the cerebral cortex that is involved in language is very extensive, as shown by intraoperative electrical stimulation, and includes not

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Figure 2.12 Schematic diagram to illustrate the course and termination of fibers originating in the inferior parietal lobule and the prefrontal cortex, and entering the middle longitudinal fasciculus (MdLF) in the white matter of the superior temporal gyrus.

only the posterior part of the superior temporal gyrus, but also the middle temporal gyrus and the inferior parietal lobule (supramarginal and angular gyri) (Penfield & Roberts, 1959; Rasmussen & Milner, 1975). Seltzer and Pandya (1984, 1994) showed that areas PFG, PG, and Opt of the inferior parietal lobule are connected with the cortex of the superior temporal gyrus and the polysensory area TPO in the superior temporal sulcus via a specific pathway running in the white matter of the superior temporal gyrus, which they named the middle longitudinal fasciculus (MdLF) (Figure 2.12). This pathway is bidirectional in nature, since the neurons in area TPO of the superior temporal sulcus are known to project to the inferior parietal lobule (Barnes & Pandya, 1992). Recent observations by Petrides and Pandya (2006) have shown that fibers originating from the prefrontal cortex (areas 10, 46, and 8Ad) connect with parts of the superior temporal gyrus (areas TS2 and TS3) and the superior temporal sulcus (area TPO) via the extreme capsule. In the temporal lobe, these fibers merge with those of the MdLF (Figure 2.12), which conveys information from the inferior parietal lobule to the superior temporal gyrus and sulcus, which are involved in language-related functions. The specific type of contribution conveyed by the MdLF to temporal language areas remains to be ascertained. The existence of the MdLF in man has recently been demonstrated in DT-MRI tractography (Makris et al., in press).

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Uncinate fasciculus There is a strong link between the rostral part of the superior temporal gyrus (areas TS1 and TS2) and the temporal proisocortex with the orbital frontal cortex (areas 13 and 47/12) and the medial prefrontal cortex (areas 14, 25, and 32) via the uncinate fasciculus (Figure 2.6). The orbitofrontal cortex, especially its more caudal part, and the adjacent limbic medial frontal regions are strongly connected with the amygdala (Aggleton, Burton, & Passingham, 1980; Amaral & Price, 1984; Barbas & De Olmos, 1990; Carmichael & Price, 1995), a structure that is critical for affective responses (see Aggleton, 1992, for review). Lesions of the orbitofrontal cortex in both monkeys (Butter, Snyder, & McDonald, 1970; Ruch & Shenkin, 1943) and man (Angrilli, Palomba, Cantagallo, Maietti, & Stegagno, 1999; Hornak, Rolls, & Wade, 1996; Sarazin, Pillon, Giannakopoulos, Rancurel, Samson, & Dubois, 1998) demonstrate that this region plays a major role in the regulation of behavioral responses to emotional stimuli. In a functional neuroimaging study, Frey et al. (2000) demonstrated a major increase in activity in the caudal orbitofrontal region in relation to the perception of unpleasant auditory stimuli, such as the sounds of violent car crashes. These findings suggest that the connections between the orbitofrontal cortex and the rostral superior temporal region established via the uncinate fasciculus may be critical for enabling the organism to evaluate and regulate responses to emotional auditory input. It is therefore likely that the interactions between the orbitofrontal and medial prefrontal cortex with the rostral superior temporal gyrus, and the interactions of the latter with the middle sector of the superior temporal gyrus and adjacent superior temporal sulcus enable emotional and motivational states to influence language processing. Ventromedial limbic pathways Finally, it is interesting to note that the lateral temporal cortical regions that are involved in language processing are also under the influence of medial temporal and posterior cingulate limbic areas. Thus, the rostral and middle parts of the superior temporal gyrus (TS1, TS2, and TS3) are connected with area TH of the parahippocampal gyrus, and area TPO in the upper bank of the superior temporal sulcus is connected with area TF in the medial temporal region (e.g. Blatt, Pandya, & Rosene, 2003; Seltzer & Pandya, 1976; Suzuki & Amaral, 1994a, b) (Figure 2.13). In contrast, the caudal part of the superior temporal gyrus (area Tpt) is preferentially related to retrosplenial area 30 and the caudal cingulate region (areas 23 and 31) (Morecraft, Cipolloni, StilwellMorecraft, Gedney, & Pandya, 2004; Morris, Petrides, & Pandya, 1999a; Pandya et al., 1981; Vogt & Pandya, 1987) (Figure 2.13). These connections might provide interactions of linguistic processing with medial temporal limbic regions that are known to be involved in mnemonic encoding (Milner, 1972; Mishkin, 1982; Squire & Zola-Morgan, 1991) and thus permit the

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Figure 2.13 Schematic diagram to illustrate the origin, course, and terminations of the ventromedial limbic pathways linking the rostral and middle superior temporal region with the parahippocampal region, and the caudal superior temporal region with the caudal cingulate and retrosplenial regions.

acquisition of novel verbal information. Perhaps, the parahippocampal cortical connections underlie aspects of verbal declarative memory, whereas the cingulate/retrosplenial areas may permit certain kinds of interactions needed for working and spatial memory (see Morris, Pandya & Petrides, 1999b). It

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remains for future studies to clarify the role of these connections in the interaction between linguistic processing and mnemonic processing. The complex sets of processes that are subsumed under the term “language” are the result of computations in widely distributed neural networks. Luigi Vignolo was never comfortable with the basic diagrams depicting only Wernicke’s and Broca’s areas, and the arcuate fasciculus as the main mode of interaction between these primary language regions. In this chapter, we have outlined an alternative proposal with several possible pathways, some being directly involved in language processing and others playing an indirect role in metalinguistic information processing. Future research will undoubtedly unravel the subtleties of the connectional pathways of the human brain involved in language, a topic that was dear to Professor Vignolo.

Acknowledgement We thank Ms Veronika Zlatkina for preparing the figures.

References Aggleton, J. P. (1992). The amygdala: Neurobiological aspects of emotion, memory, and mental dysfunction. New York: Wiley-Liss Inc. Aggleton, J. P., Burton, M. J., & Passingham, R. E. (1980). Cortical and subcortical afferents to the amygdala of the rhesus monkey. Brain Research, 190, 347–368. Alexander, M. P., & Schmitt, M. A. (1980). The aphasia syndrome of stroke in the left anterior cerebral artery territory. Archives of Neurology, 37, 97–100. Amaral, D. G., & Price, J. L. (1984). Amygdalo-cortical projections in the monkey (Macaca fascicularis). Journal of Comparative Neurology, 230, 465–496. Amunts, K., Schleicher, A., Ditterich, A., & Zilles, K. (2004). Broca’s region: Cytoarchitectonic asymmetry and developmental changes. Journal of Comparative Neurology, 465, 72–89. Amunts, K., Schleicher, A., Bürgel, U., Mohlberg, H., Uylings, H. B. M., & Zilles, K. (1999). Broca’s region revisited: Cytoarchitecture and intersubject variability. Journal of Comparative Neurology, 412, 319–341. Amunts, K., Weiss, P. H., Mohlberg, H., Pieperhoff, P., Eickhoff, S., Gurd, J. M., et al. (2004). Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—the roles of Brodmann areas 44 and 45. NeuroImage, 22, 42–56. Angrilli, A., Palomba, D., Cantagallo, A., Maietti, A., & Stegagno, L. (1999). Emotional impairment after right orbitofrontal lesion in a patient without cognitive deficits. Neuroreport, 10, 1741–1746. Azuma, M., & Suzuki, H. (1984). Properties and distribution of auditory neurons in the dorsolateral prefrontal cortex of the alert monkey. Brain Research, 298, 343–346. Bailey, P., Bonin, G., Garol, H. W., & McCulloch, W. S. (1943). Long association fibers in cerebral hemispheres of monkey and chimpanzee. Journal of Neurophysiology, 6, 129–134. Bailey, P., Bonin, G., Davis, E. W., Garol, H. W., & McCulloch, W. S. (1944). Further observations on associational fibers in the brain of Macaca mulatta. Journal of Neuropathology and Experimental Neurology, 3, 413–415.

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Baylis, G. C., Rolls, E. T., & Leonard, C. M. (1987). Functional subdivisions of the temporal lobe neocortex. Journal of Neuroscience, 7, 330–342. Barbas, H., & De Olmos, J. (1990). Projections from the amygdala to basoventral and mediodorsal prefrontal regions in the rhesus monkey. Journal of Comparative Neurology, 300, 549–571. Barnes, C. L., & Pandya, D. N. (1992). Efferent cortical connections of multimodal cortex of the superior temporal sulcus in the rhesus monkey. Journal of Comparative Neurology, 318, 222–244. Bavelier, D., Corina, D., Jezzard, P., Padmanabhan, S., Prinster, A., & Braun, A. (1997). Sentence reading: A functional MRI study at 4 tesla. Journal of Cognitive Neuroscience, 9, 664–686. Benevento, L. A., Fallon, J., Davis, B. J., & Rezak, M. (1977). Auditory-visual interaction in single cells in the cortex of the superior temporal sulcus and the orbital frontal cortex of the macaque monkey. Experimental Neurology, 57, 849–872. Blatt, G. J., Pandya, D. N., & Rosene, D. L. (2003). Parcellation of cortical afferents to three distinct sectors in the parahippocampal gyrus of the rhesus monkey: An anatomical and neurophysiological study. Journal of Comparative Neurology, 466, 161–179. Broca, P. (1861). Remarques sur le siège de la faculté du langage articulé: suivies d’une observation d’aphémie. Bulletin de la Société Anatomique de Paris, 6, 330–357. Bruce, C., Desimone, R., & Gross, C. G. (1981). Visual properties of neurons in a polysensory area in superior temporal sulcus of the macaque. Journal of Neurophysiology, 46, 369–384. Buckner, R. L., Raichle, M. E., & Petersen, S. E. (1995). Dissociation of human prefrontal cortical areas across different speech production tasks and gender groups. Journal of Neurophysiology, 74, 2163–2173. Butter, C. M., Snyder, D. R., & McDonald, J. A. (1970). Effects of orbital frontal lesions on aversive and aggressive behaviors in rhesus monkeys. Journal of Comparative and Physiological Psychology, 72, 132–144. Cadoret, G., Pike, G. B., & Petrides, M. (2001). Selective activation of the ventrolateral prefrontal cortex in the human brain during active retrieval processing. European Journal of Neuroscience, 14, 1164–1170. Campbell, J. S., Siddiqi, K., Rymar, V. V., Sadikot, A. F., & Pike, B. (2005). Flow-based fiber tracking with diffusion tensor and q-ball data: validation and comparison to principal diffusion direction techniques. NeuroImage, 27, 725–736. Carmichael, S. T., & Price, J. L. (1995). Limbic connections of the orbital and medial prefrontal cortex in macaque monkeys. Journal of Comparative Neurology, 363, 615–641. Catani, M., Jones, D. K., & ffytche, D. H. (2005). Perisylvian language networks of the human brain. Annals of Neurology, 57, 8–16. Cavada, C., & Goldman-Rakic, P. S. (1989). Posterior parietal cortex in rhesus monkey. II. Evidence for segregated corticocortical networks linking sensory and limbic areas with the frontal lobe. Journal of Comparative Neurology, 287, 422– 445. Cowan, W. M., Gottlieb, D. I., Hendrickson, A. E., Price, J. L., & Woolsey, T. A. (1972). The autoradiographic demonstration of axonal connections in the central nervous system. Brain Research, 37, 21–51. Croxson, P. L., Johansen-Berg, H., Behrens, T. E. J., Robson, M. D., Pinsk, M. A., Gross, C. G., et al. (2005). Quantitative investigation of connections of the prefrontal

46

Petrides and Pandya

cortex in the human and macaque using probabilistic diffusion tractography. Journal of Neuroscience, 25, 8854–8866. Cunnington, R., Windischberger, C., Deecke, L., & Moser, E. (2003). The preparation and readiness for voluntary movement: a high-field event-related fMRI study of the Bereitschafts-BOLD response. NeuroImage, 20, 404–412. Deacon, T. W. (1992). Cortical connections of the inferior arcuate sulcus cortex in the macaque monkey brain. Brain Research, 573, 8–26. Deecke, L. & Kornhuber, H. H. (1978). An electrical sign of participation of the mesial “supplementary” motor cortex in human voluntary finger movement. Brain Research, 159, 473–476. Dejerine, J. (1891). Sur un cas de cécité verbale avec agraphie suivi d’autopsie. Mémoires de la Société Biologique, 3, 197–201. Dejerine, J. (1892). Contribution à l’étude anatomo-pathologique et clinique des differentes variétées de cécité-verbale. Mémoires de la Société Biologique, 4, 61–90. Dejerine, J. (1895). Anatomie des centres nerveux (vol. 1). Paris: Rueff. Dejerine, J. J. (1914). Sémiologie des affections du système nerveux. Paris: Masson et Cie. Desimone, R., & Gross, C. G. (1979). Visual areas in the temporal cortex of the macaque. Brain Research, 178, 363–380. Dusser de Barrene, J. G., Garol, H. W., & McCulloch, W. S. (1941). Physiological neuronography of the cortico-striatal connections. Research Publications of the Association for Nervous and Mental Disorders, 21, 246–266. Fiez, J. A., Raife, E. A., Balota, D. A., Schwarz, J. P., Raichle, M. E., & Petersen, S. E. (1996). A positron emission tomography study of the short-term maintenance of verbal information. Journal of Neuroscience, 16, 808–822. French, J. D., Sugar, O., & Chusid, J. D. (1948). Cortico-cortical connections of the superior bank of the sylvian fissure in the monkey (Macaca mulatta). Journal of Neurophysiology, 11, 185–193. Frey, S., Kostopoulos, P., & Petrides, M. (2000). Orbitofrontal involvement in the processing of unpleasant auditory information. European Journal of Neuroscience, 12, 3709–3712. Fullerton, B. C., & Pandya, D. N. (2007). Architectonic analysis of the auditoryrelated areas of the superior temporal region in human brain. Journal of Comparative Neurology, 504, 470–498. Geschwind, N. (1965). Disconnection syndromes in animals and man. Brain, 88, 237–294. Geschwind, N. (1970). The organization of the language and the brain. Science, 170, 940–944. Geschwind, N. (1974). Selected papers on language and the brain. Boston: D. Reidel Publishing Co. Hackett, T. A., Stepniewska, I., & Kaas, J. H. (1999). Prefrontal connections of the parabelt auditory cortex in macaque monkeys. Brain Research, 817, 45–58. Hackett, T. A., Preuss, T. M., & Kaas, J. H. (2001). Architectonic identification of the core region in auditory cortex of macaques, chimpanzees, and humans. Journal of Comparative Neurology, 441, 197–222. Hikosaka, K., Iwai, E., Saito, H.-A., & Tanaka, K. (1988). Polysensory properties of neurons in the anterior bank of the caudal superior temporal sulcus of the macaque monkey. Journal of Neurophysiology, 60, 1615–1637. Hornak, J., Rolls, E. T., & Wade, D. (1996). Face and voice expression identification in

2. Neural circuitry underlying language

47

patients with emotional and behavioural changes following ventral frontal lobe damage. Neuropsychologia, 34, 247–261. Hyvarinen, J., & Shelepin, Y. (1979). Distribution of visual and somatic functions in the parietal associative area 7 of the monkey. Brain Research, 169, 561–564. Johansen-Berg, H., Behrens, T. E. J., Robson, M. D., Drobnjak, I., Rushworth, M. F. S., Brady, J. M., et al. (2004). Changes in connectivity profiles define functionally distinct regions in human medial frontal cortex. Proceedings of the National Academy of Sciences of the USA, 101, 13335–13340. Jonas, S. (1981). The supplementary motor region and speech emission. Journal of Communication Disorders, 14, 349–373. Kaas, J., & Hackett, T. (2002). Subdivisions of auditory cortex and processing streams in primates. Proceedings of the National Academy of Sciences of the USA, 97, 11800–11806. Kimura, D. (1993). Neuromotor mechanisms in human communication. New York: Oxford University Press. Klein, D., Milner, B., Zatorre, R. J., Meyer, E., & Evans, A. C. (1995). The neural substrates underlying word generation: A bilingual functionalimaging study. Proceedings of the National Academy of Sciences of the USA, 92, 2899–2903. Kostopoulos, P., & Petrides, M. (2003). The mid-ventrolateral prefrontal cortex: insights into its role in memory retrieval. European Journal of Neuroscience, 17, 1489–1497. Leinonen, L., Hyvarinen, J., Nyman, G., & Linnankoski, I. (1979). Functional properties of neurons in lateral part of associative area 7 in awake monkeys. Experimental Brain Research, 34, 299–320. Leinonen, L., Hyvarinen, J., & Sovijarvi, A. R. A. (1980). Functional properties of neurons in the temporo-parietal association cortex of awake monkeys. Experimental Brain Research, 39, 203–215. Lichtheim, L. (1885). On aphasia. Brain, 7, 433–484. Makris, N., Kennedy, D. N., McInerney, S., Sorensen, A. G., Wang, R., Caviness, V. S., et al. (2005). Segmentation of subcomponents within the superior longitudinal fascicle in humans: A quantitative, in vivo, DT-MRI study. Cerebral Cortex, 15, 854–869. Makris, N., Papadimitriou, G. M., Sorg, S., Kennedy, D., Caviness, V. S., & Pandya, D. N. (in press). The middle longitudinal fascicle in humans: A quantitative, in vivo, DT-MRI study. Cortex. Masdeau, J. C., Schoene, W. C., & Funkenstein, H. (1978). Aphasia following infarction of the left supplementary motor area. Neurology, 28, 1220–1223. Milner, B. (1972). Disorders of learning and memory after temporal lobe lesions in man. Clinical Neurosurgery, 19, 421–446. Mishkin, M. (1982). A memory system in the monkey. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 298, 85–95. Morecraft, R. J., Cipolloni, P. B., Stilwell-Morecraft, K. S., Gedney, M. T., & Pandya, D. N. (2004). Cytoarchitecture and cortical connections of the posterior cingulate and adjacent somatosensory fields in the rhesus monkey. Journal of Comparative Neurology, 469, 37–69. Mori, S., & van Zijl, P. C. (2002). Fiber tracking: Principles and strategies—a technical review. MNR Biomedicine, 15, 468–480. Morris, R., Petrides, M., & Pandya, D. N. (1999a). Architecture and connections of

48

Petrides and Pandya

retrosplenial area 30 in the rhesus monkey (Macaca mulatta). European Journal of Neuroscience, 11, 2506–2518. Morris, R., Pandya, D. N., & Petrides, M. (1999b). Fiber system linking the middorsolateral frontal cortex with the retrosplenial/presubicular region in the rhesus monkey. Journal of Comparative Neurology, 407, 183–192. Nauta, W. J. H. (1957). Silver impregnation of degenerating axons. In W. F. Windle (Ed.), New research techniques of neuroanatomy (pp. 17–26). Springfield, IL: Tomas. Pandya, D. N., & Sanides, F. (1973). Architectonic parcellation of the temporal operculum in the rhesus monkey and its projection pattern. Zeitschrift für Anatomie und Entwicklungsgeschichte, 139, 127–161. Pandya, D. N., Van Hoesen, G. W., & Mesulam, M.-M. (1981). Efferent connections of the cingulate gyrus in the rhesus monkey. Experimental Brain Research, 42, 319–330. Paulesu, E., Frith, C. D., & Frackowiak, R. S. J. (1993). The neural correlates of the verbal component of working memory. Nature, 362, 342–345. Penfield, W., & Roberts, L. (1959). Speech and brain mechanisms. Princeton, NJ: Princeton University Press. Petersen, S. E., Fox, P. T., Posner, M. I., Mintun, M., & Raichle, M. E. (1988). Positron emission tomography studies of the cortical anatomy of single word processing. Nature, 331, 585–589. Petrides, M. (1994). Frontal lobes and working memory: Evidence from investigations of the effects of cortical excisions in nonhuman primates. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology (vol. 9, pp. 59–82). Amsterdam: Elsevier. Petrides, M. (1996). Specialized systems for the processing of mnemonic information within the primate frontal cortex. Philosophical Transactions of the Royal Society of London. Series B. Biological Sciences, 351, 1455–1462. Petrides, M. (2006). Broca’s area in the human and the non-human primate brain. In A. Amunts & Y. Grodzinsky (Eds.), Broca’s region (ch. 3, pp. 31–46). Oxford: Oxford University Press. Petrides, M., & Iversen, S. D. (1978). The effect of selective anterior and posterior association cortex lesions in the monkey on performance of a visual-auditory compound discrimination test. Neuropsychologia, 16, 527–537. Petrides, M., & Pandya, D. N. (1984). Projections to the frontal cortex from the posterior parietal region in the rhesus monkey. Journal of Comparative Neurology, 228, 105–116. Petrides, M., & Pandya, D. N. (1988). Association fiber pathways to the frontal cortex from the superior temporal region in the rhesus monkey. Journal of Comparative Neurology, 273, 52–66. Petrides, M., & Pandya, D. N. (1994). Comparative cytoarchitectonic analysis of the human and the macaque frontal cortex. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology (vol. 9, pp. 17–58). Amsterdam: Elsevier. Petrides, M., & Pandya, D. N. (1999). Dorsolateral prefrontal cortex: Comparative cytoarchitectonic analysis in the human and the macaque brain and corticocortical connection patterns. European Journal of Neuroscience, 11, 1011–1036. Petrides, M., & Pandya, D. N. (2002a). Association pathways of the prefrontal cortex and functional observations. In D. T. Stuss & R. T. Knight (Eds.), Principles of frontal lobe function (ch. 3, pp. 31–50). New York: Oxford University Press.

2. Neural circuitry underlying language

49

Petrides, M., & Pandya, D. N. (2002b). Comparative cytoarchitectonic analysis of the human and the macaque ventrolateral prefrontal cortex and corticocortical connection patterns in the monkey. European Journal of Neuroscience, 16, 291– 310. Petrides, M., & Pandya, D. N. (2004). The frontal cortex. In G. Paxinos & J. K. Mai (Eds.), The human nervous system (2nd ed., ch. 25, pp. 950–972). San Diego, CA: Elsevier Academic Press. Petrides, M., & Pandya, D. N. (2006). Efferent association pathways originating in the caudal prefrontal cortex in the macaque monkey. Journal of Comparative Neurology, 498, 227–251. Petrides, M., & Pandya, D. N. (2007). Efferent association pathways from the rostral prefrontal cortex in the macaque monkey. Journal of Neuroscience, 27, 11573– 11586. Petrides, M., Alivisatos, B., & Evans, A. C. (1995). Functional activation of the human ventrolateral frontal cortex during mnemonic retrieval of verbal information. Proceedings of the National Academy of Sciences of the USA, 92, 5803–5807. Petrides, M., Alivisatos, B., & Frey, S. (2002). Differential activation of the human orbital, mid-ventrolateral and mid-dorsolateral prefrontal cortex during the processing of visual stimuli. Proceedings of the National Academy of Sciences of the USA, 99, 5649–5654. Petrides, M., Cadoret, G., & Mackey, S. (2005). Orofacial somatomotor responses in the macaque monkey homologue of Broca’s area. Nature, 435, 1235–1238. Poldrack, R. A., Wagner, A. D., Prull, M. W., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. E. (1999). Functional specialization for semantic and phonological processing in the left inferior prefrontal cortex. NeuroImage, 10, 15–35. Pribram, K. H., & MacLean, P. D. (1953). Neuronographic analysis of medial and basal cerebral cortex; monkey. Journal of Neurophysiology, 16, 324–340. Price, C. J., Moore, C. J., & Frackowiak, R. S. J. (1996). The effect of varying stimulus rate and duration on brain activity during reading. NeuroImage, 3, 40–52. Price, C. J., Moore, C. J., Humphreys, G. W., & Wise R. J. S. (1997). Segregating semantic from phonological processes during reading. Journal of Cognitive Neuroscience, 9, 727–733. Rasmussen, T., & Milner B. (1975). Clinical and surgical studies of the cerebral speech areas in man. In K. J. Zulch, O. Creutzfeldt, & G. C. Galbraith (Eds.), Cerebral localization (pp. 238–257). Berlin: Springer-Verlag. Robinson, C. J., & Burton, H. (1980). Organization of somatosensory receptive fields in cortical areas 7b, retroinsula, postauditory, granular insula of M. fascicularis. Journal of Comparative Neurology, 192, 69–92. Romanski, L. M., Bates, J. F., & Goldman-Rakic, P. S. (1999). Auditory belt and parabelt projections to the prefrontal cortex in the rhesus monkey. Journal of Comparative Neurology, 403, 141–157. Rubens, A. B. (1975). Aphasia with infarction in the territory of the anterior cerebral artery. Cortex, 11, 239–250. Ruch, T. C., & Shenkin, H. A. (1943). The relation of area 13 on orbital surface of frontal lobes to hyperactivity and hyperphagia in monkeys. Journal of Neurophysiology, 6, 349–360. Sarazin, M., Pillon, B., Giannakopoulos, P., Rancurel, G., Samson, Y., & Dubois, B. (1998). Clinicometabolic dissociation of cognitive functions and social behavior in frontal lobe lesions. Neurology, 51, 142–148.

50

Petrides and Pandya

Seltzer, B., & Pandya, D. N. (1976). Some cortical projections to the parahippocampal area in the rhesus monkey. Experimental Neurology, 50, 146–160. Seltzer, B., & Pandya, D. N. (1978). Afferent cortical connections and architectonics of the superior temporal sulcus and surrounding cortex in the rhesus monkey. Brain Research, 149, 1–24. Seltzer, B., & Pandya, D. N. (1984). Further observations on parieto-temporal connections in the rhesus monkey. Experimental Brain Research, 55, 301–312. Seltzer, B., & Pandya, D. N. (1994). Parietal, temporal, and occipital projections to cortex of the superior temporal sulcus in the rhesus monkey. Journal of Comparative Neurology, 343, 445–463. Squire, L. R., & Zola-Morgan, S. (1991). The medial temporal lobe memory system. Science, 253, 1380–1386. Sugar, O., French, J. D., & Chusid, J. D. (1948). Cortico-cortical connections of the superior surface of the temporal operculum in the macaque (Macaca mulatta). Journal of Neurophysiology, 11, 175–185. Suzuki, H. (1985). Distribution and organization of visual and auditory neurons in the monkey prefrontal cortex. Vision Research, 25, 465–469. Suzuki, W. A., & Amaral, D. G. (1994a). Perirhinal and parahippocampal cortices of the macaque monkey: Cortical afferents. Journal of Comparative Neurology, 350, 497–533. Suzuki, W. A., & Amaral, D. G. (1994b). Topographic organization of the reciprocal connections between the monkey entorhinal cortex and the perirhinal and parahippocampal cortices. Journal of Neuroscience, 14, 1856–1877. Taira, M., Mine, S., Georgopoulos, A. P., Murata, A., & Tanaka, Y. (1990). Parietal cortex neurons of the monkey related to the visual guidance of hand movement. Experimental Brain Research, 83, 29–36. Tian, B., Reser, D., Durham, A., Kustov, A., & Rauschecker, J. P. (2001). Functional specialization in the rhesus monkey auditory cortex. Science, 292, 290–293. Vaadia, E., Benson, D. A., Hienz, R. D., & Goldstein, M. H. (1986). Unit study of monkey frontal cortex. Active localization of auditory and of visual stimuli. Journal of Neurophysiology, 56, 934–952. Vogt, B. A., & Pandya, D. N. (1987). Cingulate cortex of the rhesus monkey. II. Cortical afferents. Journal of Comparative Neurology, 262, 271–289. Wallace, M. N., Johnston, P. W., & Palmer, A. R. (2002). Histochemical identification of cortical areas in the auditory region of the human brain. Experimental Brain Research, 143, 499–508. Ward, A. A., Peden, J. K., & Sugar, O. (1946). Corticocortical connections in the monkey with special reference to area 6. Journal of Neurophysiology, 9, 453–462. Warren, J. D., Zielinski, B. A., Green, G. G. R., Rauschecker, J. P., & Griffiths, T. D. (2002). Perception of sound-source motion by the human brain. Neuron, 34, 139–148. Wernicke, C. (1874). Der aphasische Symptomencomplex. Breslau, Poland: Cohen and Weigert. Zatorre, R. J., Bouffard, M., Ahad, P., & Belin, P. (2002). Where is “where” in the human auditory cortex? Nature Neuroscience, 5, 905–909.

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Structural and functional neuroimaging in neuropsychology A concise overview Jubin Abutalebi, Lisa Bartha Doering, Pasquale Anthony Della Rosa, and Peter Mariën

The lesion-behavior method For more than a century, the lesion-behavior method has grounded the development of insights in the functional anatomy of the brain and the neural organization of cognitive functions. The attempt to establish a direct relation between injury in a specific brain region and cognitive manifestations dates back to Jean-Baptiste Bouillaud (1825), who linked disruption of oral language functions in a series of aphasic patients to postmortem findings of frontal lobe damage. The modern era of anatomoclinical insights in neuropsychological and neurobehavioral syndromes started in the 1860s in Paris with Paul Broca’s seminal contributions to the Société d’Anthropologie. In the course of 4 years of intensive discussions about the representation of language functions in the brain, Broca presented clinical and neuroanatomical evidence that established a correlation between expressive aphasia and damage to the frontal region of the language-dominant hemisphere (that is, the left hemisphere in dextrals and the right hemisphere in sinistrals). New concepts and methods of investigation exposed during the debates on the localization of speech rapidly extended to other aspects of language and related cognitive areas. During the last decades of the nineteenth century, vigorous application of the lesion-behavior method led to several innovative insights and influential discoveries in the understanding of brain–behavior relationships. In 1874, the German neurologist Carl Wernicke introduced the prototype of fluent aphasia that substantially differed from Broca’s nonfluent, expressive variant following frontal lobe damage. In his monograph Der aphasische Symptomencomplex, Wernicke (1874) described what he called “sensory aphasia” following structural damage to the posterior part of the superior temporal gyrus of the language-dominant hemisphere. In addition, Wernicke identified global aphasia and conduction aphasia on the basis of a model that explained aphasic syndromes as the result of lesions affecting different, noncontiguous language centers and their unidirectional anatomical connections capable of performing a variety of complex functions with relative independence. During

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the last decades of the nineteenth century, a considerable expansion of knowledge about specific aspects of aphasia and related disorders was realized. Déjerine (1892), for instance, elucidated the neuranatomic substrate of pure alexia, Brissaud (1894) described the phenomenon of prosodic speech disturbances (aphasie d’intonation), and Pitres called attention to aphasia in polyglots (Pitres, 1895) and to the syndrome of amnestic aphasia (Pitres, 1898). In this period of intense experimental, clinical, and anatomoclinical activity, a variety of neuropsychological functions and skills were localized as well. Munk (1878) first identified “cortical blindness” and “mindblindedness” as examples of higher-level impairment of visual perception and recognition after occipital lobe lesions. Freud (1891) coined the term “agnosia” to denote the phenomenon of disrupted recognition skills. Astereognosis as the somesthetic counterpart of visual agnosia was described by Hoffmann (1885) and related to damage of the postcentral gyrus by Wernicke (1895). Diverse forms of apraxia after focal lesions of the language-dominant hemisphere were described during the first decades of the twentieth century (Liepmann, 1900; Strauss, 1924). By contrast, the early scattered attempts to demonstrate that the nondominant right hemisphere also possesses some distinctive functional qualities in the regulation of cognitive behavior had no significant influence on the development of neuropsychological knowledge until after World War II. Although the nineteenth-century connectionist framework succeeded in explaining a variety of neurocognitive syndromes such as aphasia, agraphia, alexia, agnosia, apraxia, and amnesia, its theoretical substrate was fundamentally criticized by the “holists”, who strongly rejected the view of the nervous system as a series of functionally independent centers connected by unidirectional pathways. One of the most influential skeptics of localizationalism was the English neurologist John Hughlings Jackson (1835–1911), who regarded the nervous system as a hierarchically organized and functionally interactive mechanism that could not be broken down into pieces. Hughlings Jackson’s (1878) often-quoted assertion that “to locate the lesion which destroys speech and to locate speech are two different things” summarizes the criticism of the anti-localizationalists. Because of its strong association with the theory of localizationalism, the lesion-behavior approach, as a principal means to investigate the neural substrate of human behavior and cognition, was largely abandoned soon after the turn of the century. The innovative work of leading behavioral neuroscientists such as Arthur Benton, Norman Geschwind, Henri Hécaen, Alexandrej Luria, Brenda Milner, Hans-Lukas Teuber, and Oliver Zangwill gradually established a revival of the lesionbehavior method from the 1960s onward as a reaction to the tradition of antilocalizationalism and “black-box” behaviorism. While most of the advances in brain–behavior relationships before the 1960s had been achieved by studying individual or small cohorts of patients without quantitative measures, neurologists and neuropsychologists in the 1960s started to develop experimental designs patterned on research methods applied in experimental psychology

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to investigate a variety of cognitive skills such as intelligence, language, attention, memory, praxis, gnosis, perception, and executive functions. Large groups of patients with different lesion distributions and neurocognitive syndromes were studied by means of standardized test batteries, yielding quantitative results that could be statistically compared across patient groups and control groups.

Structural neuroimaging The advent of modern neuroimaging at the beginning of the 1970s solidly reinstalled and even revolutionized the application of the lesion-behavior approach in the cognitive and behavioral neurosciences. Growing sophistication of neuroimaging techniques and further refinement of the methods and instruments to assess and quantify neurobehavioral characteristics substantially advanced insights in brain–behavior relationships during the past three decades. The inception of computerized X-ray axial tomography (CT) in 1973 and magnetic resonance imaging (MRI) of the brain less than a decade later opened a new avenue to define with much precision the anatomic substrate of behavioral and cognitive disorders in living subjects at the time the deficit appeared or at any time later in the course of the disease. The application of CT scanning in the study of aphasic syndromes was introduced by Naeser and Hayward (1978); Damasio, Damasio, Hamsher, and Varney (1979); Kertesz, Harlock, and Coates (1979); and Mazzocchi and Vignolo (1979). Evaluation of classical aphasiological concepts with CT yielded some unexpected results and refinement of the classical insights in lesion–aphasia correlations. Studies, for instance, showed that cerebral damage confined to Broca’s area (Brodmann areas 44 and 45) is more likely to produce apraxia of speech than Broca’s aphasia, which results only from larger and deeper lesions involving Broca’s area and the adjacent posterior frontal and anterior parietal region. Although most of the lesion-behavior studies in the 1970s and 1980s were devoted to a critical evaluation of traditional autopsy-based models of language localization and aphasia typology, the pioneer studies of the 1970s and 1980s had already succeeded in extending the view of the anatomic substrate of aphasia beyond the boundaries of the perisylvian region of the language-dominant hemisphere. The use of structural neuroimaging techniques in aphasia research rapidly led to irrefutable evidence of the existence of the much debated subcortical and thalamic aphasias (Cappa & Vignolo, 1979; Damasio, Damasio, Rizzo, Varney, & Gersh, 1982; Mohr, 1983; Naeser, 1983). Structural neuroimaging not only had a major impact on the understanding of the cerebral representation of language functions but also substantially contributed to the expansion of knowledge in other cognitive domains such as the neural basis of memory, visuoperceptive skills, praxis, and executive functions (see Damasio & Damasio, 1989, for a review).

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Functional neuroimaging Principles The search to understand the functional organization of the human brain by means of techniques that assess changes in cerebral blood flow has occupied neuroscience for more than a century. William James’ (1890) monumental, two-volume Principles of Psychology refers to the work of the Italian physiologist Angelo Mosso (1881), who recorded the pulsation of the human cortex in patients with skull defects following neurosurgical procedures. Mosso (1881) showed that these pulsations increase regionally during mental activity and concluded that blood circulation changes selectively with neuronal activity. Despite a promising start, interest in this research area virtually ceased during the first quarter of the twentieth century. The advent of structural brain-imaging techniques in the 1970s reopened this research area. Structural neuroimaging techniques, although of crucial clinical importance, provide anatomic and structural information but do not inform us about the functioning of the brain. In recent years, functional neuroimaging, broadly defined as techniques that provide measures of brain activity, has further increased the ability to study the neural basis of human behavior. The modern era of functional brain imaging started with the use of positron emission tomography (PET) and single-photon emission computerized tomography (SPECT). Functional magnetic resonance imaging (fMRI) emerged a few years later as an extremely powerful and safe technique to study the anatomic substrate of motor and cognitive processes. There are many ways to visualize the working human brain. One of the techniques used by PET is a radioactive tracer administered to the subject in order to measure cerebral metabolism, cerebral blood flow, or neuroreceptorsneurotransmitters. A large part of metabolic cerebral needs (and, therefore, of glucose consumption) serve to maintain synaptic activity. Since the brain does not have the ability to store oxygen and glucose, the intake of these energy resources through cerebral blood flow is crucial to guarantee constant neural activity. It has been shown that, under normal conditions, there is a high level of coupling between energy metabolism and regional cerebral flow (rCBF) (Sokoloff, 1975), even though a number of experiments demonstrated that the increase in rCBF exceeds the local energy demand (Fox & Raichle, 1986). This observation is important because it shows that changes in regional blood flow can provide more meaningful information than direct measurements of cerebral metabolism. PET PET is a technology that creates images of the distribution of radiation in the brain within the central opening of a doughnut-shaped PET scanner. To obtain measurements of functional parameters, such as rCBF and glucose

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consumption, PET scanning needs the combination of three basic requirements: (1) a PET scanner; (2) a cyclotron (an accelerator of particles which produce positron-emitting radiotracers), and (3) a method of data analysis. Radioactive substances, called tracers, are employed to “image” different physiological processes, such as brain blood flow or metabolism (that is, glucose consumption). Indeed, PET shows a three-dimensional (3-D) brain distribution of positron-emitting radiotracers attached to molecules, such as fluorinedeoxyglucose when the measurements refer to glucose consumption, or to water molecules when the measurements refer to rCBF. In the latter case, areas of higher blood flow have a larger amount of radioactive tracer, and thus emit a stronger signal. It should be underlined that blood flow is an indirect measure of local synaptic activity. Regarding the study of cognitive functions, most studies investigating rCBF increase (cerebral activation) linked to the performance on cognitive tasks (such as language, memory, and attention) have employed labeled oxygen (15O2) as radiotracer; that is, oxygen from which an electron has been removed from its atom to create an unstable compound capable of emitting positrons. The 15O2 is used in the form of water (H215O) and is administered intravenously to the subject. The advantage of this tracer is that it decays in a short period of time (approximately 2 min). As a result, several scans (up to 16) can be made during a single session before the decay of the tracer starts, enabling researchers to study different conditions while patients carry out different tasks. At the beginning of each PET scan procedure, a small amount of labeled water is venously injected while the subject is positioned in the scanner. After about 30 s, the tracer starts to appear in the brain and the next 30 s, when radiation has reached its peak in the brain, constitutes the “critical window”. Images of rCBF are obtained during this “critical window” phase. By data analysis methods, a 3-D representation of the brain is obtained in the form of a mapping of radioactivity distribution, which indicates cerebral activity linked to the task performed during scanning. SPECT SPECT also uses radiotracers (usually containing iodine) incorporated in biologically active compounds whose distribution is studied at the brain level. This technique makes it possible to study the cerebral blood flood in tissues with an intense metabolic activity. Like PET, the term SPECT was derived from the type of radioisotopes utilized in the scanning procedure. In this case, the isotopes produce a single photon when they decay. The radioisotopes used for SPECT are available on the market and do not require the use of a cyclotron to fabricate the tracer. For this reason, SPECT scanning has become more widespread and more commonly used than PET scanning. However, as SPECT images depend on the release of a single photon, its spatial resolution is considerably poorer than that obtained with PET scans. SPECT is frequently applied to study dementia, and Alzheimer’s disease in

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particular, where a decrease in frontal and bilateral temporal-parietal cerebral blood flow has been proven (Perani et al., 1988a). Moreover, SPECT scans have highlighted an excellent correlation between the neuropsychological pattern and a decrease in cerebral blood flow in patients with vascular lesions and those suffering from aphasia (Perani, Papagno, Cappa, Gerundini, & Fazio, 1988b), in patients with isolated, progressive cognitive deficiencies (Cappa et al., 1993), and in patients suffering from Parkinson’s disease with or without associated dementia (Antonini, De Notaris, Benti, De Gaspari, & Pezzoli, 2001). Although the techniques of PET and SPECT are more widely applied in clinical diagnostics due to cost-effectiveness (in particular the SPECT technique) and user-friendliness, their use in neuropsychology research is rather limited. In many research centers, application of SPECT and PET is restricted to study groups of neurological patients, as healthy subjects often cannot be investigated because of ethical considerations. Furthermore, PET and SPECT techniques have poor spatial resolution compared with structural images and a low signal-to-noise ratio in the activation images. fMRI The main reason why fMRI rapidly became extremely popular and widely applied in neuropsychological research is that this noninvasive technique does not require exposure of the subject to radiation. It is therefore particularly suitable for cognitive activation studies in normal subjects and patients. The two most important characteristics of fMRI are the high spatial resolution typical of magnetic resonance (MR) and the ability to visualize areas of the brain while subjects perform a cognitive task. The principle underlying MR is the particular property of certain atomic nuclei, when positioned in a magnetic field and stimulated by radio waves at characteristic frequencies, to re-release part of the energy absorbed in the form of a magnetic signal (the MR signal). The properties of the hydrogen nucleus are most commonly used for clinical structural MR purposes, while fMRI uses the paramagnetic properties of deoxyhemoglobin, as illustrated below. Ultrarapid image acquisition techniques, termed EPI (echo planar imaging), make it possible to measure the changes in blood oxygenation that occur during cerebral activation tasks. This is known as the BOLD (Blood Oxygenation Level Dependent) effect. In case of functional activation (as via a cognitive or sensorimotor task), a local increase in cerebral blood perfusion occurs, inducing an increase in the quantity of oxyhemoglobin (the oxygenated form of hemoglobin) that reaches the capillary district. However, as oxygen is not completely used by the tissue in an activation state, a greater amount of oxyhemoglobin consequently reaches the venous side of the capillary district where deoxyhemoglobin (the deoxygenated form of hemoglobin) usually prevails. Given that deoxyhemoglobin, unlike oxyhemoglobin, is a

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paramagnetic substance, a temporary local reduction occurs in the magnetic sensitivity generated by deoxyhemoglobin. As the concentration of deoxyhemoglobin decreases to the detriment of oxyhemoglobin concentration in the activation phase, an increase in signal intensity is observed. In other words, it is the oxygen itself that acts as an endogenous contrast medium. In conclusion, fMRI measures blood flow and is an indirect measure of neural activity. The sluggishness of the hemodynamic response limits the effective temporal resolution of the fMRI signal to a few seconds, as opposed to the millisecond temporal resolution of electrical recordings of neural activity (such as from event-related potentials (ERPs) studies). However, several investigators have reported significant differential functional responses between two trial types with trials spaced as closely as 500 ms apart, provided that these stimuli are presented in a random fashion (Savoy et al., 1996). Some tasks, such as delayed-response tasks, have individual trial events (such as the presentation of a sentence, the delay period, and the response) whose order cannot be randomized. In these types of tasks, the temporal resolution is necessarily lower. The limited temporal resolution of fMRI does not necessarily mean that brief changes in neural activity cannot be detected with sufficient statistical power. Several investigators have reported fMRI signal changes that were correlated with short-lasting events. Thus, fMRI has superb temporal and spatial resolution, making it a powerful method of neuropsychological research. Since fMRI does not require radiation, subjects may be examined several times, and hence the experiment may be repeated many times. Early experiments with fMRI were designed to study the reliability of the method and to evaluate how the BOLD signal correlates with cerebral flow measured with PET. Soon after these pioneer studies, more and more complex experimental designs with increasingly articulated research objectives were conducted. Thanks to these stringent efforts, cognitive neuroscientists can now study the cerebral architecture of cognitive functions in relative detail. However, like all means of investigation, fMRI has methodological drawbacks too. Image acquisition is often confined to a “region of interest” of the brain and therefore relies on neuroanatomic prerequisites. For instances, in the landmark study of Kim et al. (1997) that was designed to investigate whether bilinguals use the same brain areas or segregated brain areas for language production in the first (L1) and in the second language (L2), the authors focused only on Broca’s and Wernicke’s area as their “regions of interest”. In addition, problems related to motion features may arise. Due to its excellent spatial resolution (under 1 mm), even minimal movements made by the patient introduce features that may alter functional results. The recent introduction of image-co-recording algorithms should reduce this problem. Moreover, image acquisition with fMRI is difficult in the orbitofrontal and inferior temporal lobe regions because of susceptibility to artifacts caused by the sinuses in the adjacent anatomic regions. However, improvements in pulse sequences for acquiring fMRI data should eventually eliminate these

58 Abutalebi et al. artifacts. Electrical recordings, such as the electromyogram (EMG) or the electro-oculogram (EOG), during fMRI scanning also present a technical challenge that has been tackled in some laboratories. The types of hypotheses that can be tested with fMRI relate to the following: • •

•

Functional specialization: the concept of functional specialization is based on the premise that functional modules exist in the brain, that is, cerebral areas that are specialized for specific cognitive processes. Testing cognitive theory: an exciting innovative direction for functional neuroimaging is illustrated by studies that use imaging data to test theories regarding underlying mechanisms of cognition, such as the concept of a critical period in which language learning is neurologically wired-in, as illustrated below. Functional integration: functional neuroimaging studies can also test hypotheses about interactions between brain regions by focusing on covariances of activation levels between regions. These covariances have been referred to as “functional connectivity”, a concept that was originally developed in reference to temporal interactions among individual cells.

How to construct a functional neuroimaging experiment The most obvious rationale for conducting functional neuroimaging experiments is to correlate structure with function. Complex neuropsychological processes are best described in terms of combinations of constituent elementary operations. These elementary processes may not be localized in single locations in the brain; rather, they are often the result of networks of neurons acting together. Exactly this consideration is the limit of the lesion-behavior approach: the lesion is usually confined to a single brain location, and inferences from the lesion site to the impaired cognitive function may be too vague. Cognition is a distributed process; hence, cognitive functions, such as language, may not be localizable in a single brain region (Berns, 1999). Most evidence points to networks of regions functioning with a particular choreography that gives rise to a cognitive function. Therefore, to study the neural basis of cognitive functions, techniques are needed that are able to measure neural function simultaneously in the entire brain. PET and fMRI provide enough spatial and temporal resolution to make plausible conclusions possible about the role of specific brain regions in cognition. In the following paragraphs, we will illustrate how to build, carry out, analyze, and interpret functional neuroimaging experiments. It is clear that before starting a neuroimaging experiment, several important issues must be taken into consideration. First, a specific and relevant hypothesis must be created; second, appropriate methods must be selected; third, the experiment must be appropriately conducted, analyzed, and interpreted. These choices

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will be constrained by the nature of the task chosen, the available imaging technology and its limitations, and the types of inference one wishes to draw from the study. Designing an experimental task The design of an experimental task limits the ultimate interpretability of the data. Tasks must be chosen that yield theoretical insight into the neuropsychological processes under investigation, and they must avoid the influence of nuisance variables. Nuisance variables may be neural processes unrelated to the question of interest, either prescribed by the task or unrelated to it. They may be physiological artifacts due to phenomena such as heart rate, respiration, and eye movements that may interfere with rCBF, or even technological artifacts. To the extent that nuisance variables influence brain activations in a task, they may have repercussions on the interpretation of the data. Constructing adequate tasks can be quite challenging, and may not be possible in some situations. Once an adequate task is created, important decisions need to be made concerning the right frame to fit around the task; that is, the experimental paradigm. This decision is constrained by the technique that will be employed and is related to the advantages and limitations linked to the physical properties underlying the detection of a specific signal. A final caveat with regard to the choice of certain cognitive paradigms is that the brain systems involved do not necessarily remain constant through many repetitions of the task. Rather, when a task is novel, major changes can occur in the systems fired by the task. Such changes have both practical and theoretical implications when it comes to the design and interpretation of cognitive activation experiments. The prevailing paradigms for analyzing task-related changes with PET or fMRI are the “blocked” paradigms and “event-related” designs. Block designs A block design is the standard experimental design used in PET activation studies because long intervals of time (30 s or more) are required to collect sufficient data to yield a good image. In such a block design, different conditions in the experiment are presented as separate blocks of trials (such as picture naming in one block and lexical decision in a different block), with each block representing one scan during the experiment. The activations of interest in a PET experiment are the activations that accumulate over the entire recording interval of a scan. If one is interested in visualizing the neural effect of some briefly triggered psychological response (such as the activation due to a flashed light stimulus), one would have to repeat the event repeatedly during a block of trials so that activations accumulate over the recording interval of a scan. The activations obtained can be compared with an appropriate

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baseline control scan in which the stimulus event does not occur. However, given its temporal limitations, PET is not well suited to examine the time course of brain activity that may change within seconds or fractions of a second. The blocked structure of PET designs is a major factor in the interpretability of results, and, most commonly, activations related to slowly changing factors such as task-set are captured in this type of design. Many fMRI studies also apply blocked designs. Again in these “blocked” paradigms, subjects alternate between performing an “active” (such as picture naming) and a “control” task (such as a rest condition) for short periods of time (e.g. 30 s). The images acquired during the active task blocks are statistically compared to the images acquired during the control task block. One advantage of using a blocked design with fMRI is that it offers more statistical power to detect a relevant change. Event-related design To take advantage of the rapid data-acquisition capabilities of fMRI, the event-related fMRI technique was developed to create images of the neural activity related to specific stimuli or cognitive events within a trial. The technique involves spacing stimuli far enough apart in time so that the hemodynamic response to a single stimulus or cognitive event is permitted to return to baseline before the onset of the next stimulus or event. Most researchers consider 14–16 s enough time for this process (Aguirre, Zarahn, & D’Esposito, 1998; Dale & Buckner, 1997). By means of this technique, signals from individual trials of the same task (such as reading single words) can be averaged together, and the time course of the hemodynamic response within a trial can be determined. This technique permits randomization of trials from different conditions (such as presenting words belonging to two different languages intermingled), which is essential for certain tasks such as language switching. It also allows researchers to analyze only selected types of trials in a mixed trial block, enabling the study of a number of processes that occur only on some trials. For instance, during a lexical decision task, an event-related design allows us to analyze only correct responses, since false responses may be discarded from the final analysis. During a block design, the latter option is not possible, and hence the brain activity may be related to both correct and false responses. The limiting factor of event-related designs lies within the temporal resolution of fMRI; that is, it is not the speed of data acquisition, but the speed of the underlying hemodynamic response to a neural event, which peaks 5–8 s after a specific neural activity has peaked. However, the recent advent of “rapid event-related fMRI techniques” has provided an adequate means to perform experiments in which successive stimuli or cognitive events can be presented in as little as 750 ms (Dale & Buckner, 1997). Importantly, potential effects of fatigue, boredom, and systematic patterns of thought unrelated to the task during long intertrial intervals are minimized with such designs. It

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is noteworthy that in employing “rapid event-related fMRI techniques” the intertrial interval must be varied from trial to trial. Without jittering the intertrial interval, the neural events would occur too rapidly to be sampled effectively. Subject selection When neuroimaging techniques are applied to make some inferences on a process of interest, it is important to use an appropriate number of subjects in order to obtain enough statistical power to allow generalization of the findings to an entire population of individuals. In addition, subjects should be controlled for age, handedness, language, and education. Depending on the fMRI experiment, further data about cognitive functions can be helpful, such as IQ, memory state, and attentional functions. Data analysis Once a task is designed and the data are collected, analysis comprises two important substages: preprocessing of the images and statistical analysis of the activations. Preprocessing refers to image processing in which the various images in a set of data must be aligned to correct for head motion that may have occurred from one image acquisition to the next. Following alignment, images are often normalized to a standard brain template (often provided by the software package) so that results from several subjects can be combined into averages and plotted into a standard 3-D brain space. Many researchers also smooth images, in order to give the noise in the images a more Gaussian distribution. This smoothing of images effectively produces a weighted average of the signal across neighboring voxels (3-D pixels). Although smoothing may decrease the spatial resolution of the images, it helps to estimate and control for statistical noise. It is useful to know that data in neuroimaging experiments are in the form of a matrix of signal intensity values in each region of the brain expressed in voxels (the smallest distinguishable box-shaped part of a 3-D image). Following these preprocessing stages, statistical tests are performed on the data. How to contrast experimental conditions? The problem of deriving conclusions about cognitive processes from neuroimaging data is that nearly any isolated task produces changes in most areas of the brain. To associate changes in brain activation with a particular cognitive process (such as a lexical decision task), changes related to that process must be isolated from changes related to other processes (for instance, related to a picture-naming task). At its simplest, the fMRI experiment can be considered a “subtraction experiment”. In a subtraction experiment, images are acquired during two different conditions (such as the lexical

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decision task and the picture-naming task). To identify “differences” between both conditions, the activations obtained in one condition are subtracted from the activations obtained in the other condition (for example, lexical decision versus picture naming, in order to illustrate what is more activated during the former task). The logic of subtraction is that if two experimental conditions that differ by only one process are investigated, subtraction of the activations of one condition from those of the other should reveal the brain regions associated with the target process (see Figure 3.1, for an example during a fluency task in a second language in different groups of bilinguals). However, as will be discussed below, a number of considerations may limit this study design. At first sight, the simplest experimental condition is between a task performed during “block A” and a “rest block” in which no task is performed. This is often referred to as the “A versus rest” design. While this is conceptually simple (the hypothesis is that there is “some” activity during block A and “no” activity during the rest block), it may be difficult to ensure that there is no confounding brain activity during the rest block (simply instructing the subject “not to think of anything” may not suffice to ensure no neural activity). An alternative approach is to set up a condition during the “rest block” to distract the subject from confounding memory, imagination, or continued activity. In fact, the “block A” versus block “rest” design can be considered a special case of the more general “block A” versus “block B” (that is, a lexical decision task in block A and a picture-naming task in block B) design, in which different activity is expected between blocks A and B, and the purpose of the analysis is to identify those differences. Clearly, this method imposes a considerable burden on the choice of an appropriate “block B” to complement “block A” without (unintentional) obscuring or canceling out activation that might be common to both. Once the experimental conditions are built in order to highlight adequately the activations elicited by different cognitive processes, the subtraction is accomplished one voxel at a time. The results of the voxel-wise subtractions yield a 3-D matrix of the difference in activation between the two conditions throughout the scanned regions of the brain. Statistical approaches A number of statistical strategies are available to analyze the data obtained in functional activation studies. In principle, the mean signal intensity can be compared on a voxel-wise basis between images acquired during “condition A” versus “rest” (or “condition B”, etc.). The significance of any observed difference can then be tested by the simple Student’s t-test. A more elegant extension of this is to compute the correlation coefficient of each voxel’s signal intensity time course against a reference “boxcar” function defined as “−1” during rest and “+1” during “condition A”. The magnitude (r) and significance level ( p value) can then be described on a voxel-wise

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basis and used as a basis for constructing color overlay maps, in which “activated pixels” are identified in color overlaid on gray-scale source images. The choice of a correlation coefficient threshold to delineate “significant” activation from “spurious” noise introduces a somewhat uncomfortable arbitrariness in the analysis. The interpretation of significance is clouded by consideration of the many multiple comparisons being made in the above simplified approach. Consider an image matrix of 128 × 128 pixels (>10,000 pixels). Assuming that a significance level of p < .05 is considered “significant”, it is clear that we might expect over 500 pixels to pass this threshold “by random chance”. But a single pixel’s signal intensity behavior is neither truly independent nor exactly dependent on other pixel responses. It is reasonable, therefore, to entertain the notion that “neighboring” pixels might have a similar underlying neuroanatomy and thus similar physiological responses, but “how neighboring” and “how similar”? These two questions clearly evoke some form of correction to the simple t statistic. The simplest approach is the Bonferroni correction method, which approximates the actual probability of n comparisons as n times the p value at any one voxel. The uncorrected (or voxelwise) p values indicate the proportion of voxels in the image that will light up by chance, while the corrected (or map-wise) p values indicate the probability of false-positive voxels occurring anywhere in the image. These represent two rather extreme viewpoints, whereas what really matters is the proportion of voxels declared as active but probably being false positives. This corresponds to the so-called false discovery rate, which has been recently incorporated into several of the standard analysis packages, although it has not yet become the standard reporting method in the literature.

Applications in neuropsychological research Activation studies aim to map brain functions in both neurologically healthy and cognitively disordered subjects. The functioning of the brain during various cognitive tasks is based on the activities of complex neural connections in which each neural network node may have a specific function. Knowledge of the anatomic substrate of cognitive functions as provided by neuropsychologically derived insights is crucial for a better understanding of the functioning of the cognitive systems that subserve memory, speech, etc. Neuroimaging techniques have widened the scope of surveys and allow us to evaluate these systems under normal conditions. In the following sections, the study of Wartenburger et al. (2003) on bilinguals is discussed as an example of how to design an fMRI experiment. The authors aimed to determine whether grammatical and semantic processing is differentially influenced by the age of second language (L2) acquisition and the degree of L2 proficiency. For the sake of brevity, we will not mention the extensive advancements achieved by functional neuroimaging studies in other neuropsychological domains such as memory, attention, visual processing, and

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Figure 3.1 The subtraction method in functional neuroimaging experiments. The figure displays the pattern of brain activity when generating words in a second language in two different groups of subjects. The conditions were a second language to which subjects of the study were less exposed (on the left) and a second language to which a different group of subjects were highly exposed (in the middle). As may be observed, more extensive brain activation in the left dorsolateral frontal cortex is found when generating words in a less exposed second language. These findings suggest that a second language associated with lower environmental exposure is in need of additional neural resources. In order to know where these additional neural resources are located, the subtraction method can be used: the brain activity pattern of the wellexposed group is subtracted from the pattern found in the group of lowexposed subjects’ brain activity. The result is illustrated on the right, and the pattern of brain activity shows those areas necessary for supporting a second language to which subjects are relatively less exposed (modified from Perani et al., 2003). Note that the subtraction method may be used either between different groups or between different conditions in the same group (that is, word generation in L1 versus L2). In our example, subtraction is used between groups. (This figure is published in color at www. psypress.com/brainscans-etc/)

neuropsychological recovery. In many of the chapters of this volume, mention is made of functional neuroimaging studies, and hence, the reader is referred to these chapters.

A brief sample of how fMRI may test a cognitive theory Wartenburger et al. (2003) aimed to study whether age of L2 acquisition or rather the degree of second language (L2) proficiency is more important for the neural representation of L2. Psycholinguistic evidence related to this issue is controversial. Theories range from the postulation of biologically based “critical periods” for some aspects of language, such as grammatical processing, to differences between infant and adult learning contexts (Birdsong, 1999; Johnson & Newport, 1989; Lenneberg, 1967). Likewise, some authors argue that, at least for lexical-semantic aspects, the level of language proficiency is more important for the mental representation of a L2 (Kroll & Stewart, 1994).

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Hence, Wartenburger et al. (2003) tried to enrich the discussion by providing neurobiological evidence of how an L2 is represented in the brain. The authors used fMRI to investigate the effects of age of acquisition (AOA) and level of proficiency (PL) on the neural correlates of grammatical and semantic processing in Italian-German bilinguals who learned L2 at different ages and showed different proficiency levels. Subjects To assess the effects of AOA and PL, three groups of healthy, adult ItalianGerman bilinguals were considered for the experiment: • • •

group 1: subjects who acquired L2 since birth and showed high proficiency for both languages (early-acquisition and high-proficiency bilinguals) group 2: subjects who acquired L2 late but showed a proficiency level comparable with group 1 (late-acquisition and high-proficiency bilinguals) group 3: subjects who learned L2 late and showed low L2 proficiency at the time of the experiment (late-acquisition and low-proficiency bilinguals).

In the experiment the groups consisted of 10 subjects on average. Stimuli and experimental paradigm The stimulus material in the experiment consisted of 180 short sentences (90 German sentences and 90 Italian sentences). Forty-four of the German and Italian sentences were semantically and grammatically correct. In both languages, the remaining 46 sentences contained either semantic (23 sentences) or grammatical (23 sentences) violations. Thus, there were four conditions: German grammatical judgment, Italian grammatical judgment, German semantic judgment, and Italian semantic judgment. A large number of stimuli within each experimental condition was necessary in order to elicit the desired effect on the cognitive process under investigation. The sentences were divided into 12 blocks (block design), lasting 128 s, resulting in three blocks for each of the four conditions. After an initial resting period (60 s), the blocks of sentences were presented in a random order. Between each block, a fixation cross appeared for 32 s indicating a rest period. Each block was made of 15 pseudorandomized correct and incorrect sentences and was preceded by an instruction sentence (e.g. grammatical judgment German). After each sentence was presented, a fixation cross was displayed for 4 s. Subjects under the scanner were asked to judge whether sentences in both L1 and L2 were semantically or grammatically correct and were asked to indicate by a right-hand button press when they identified a correct sentence.

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Data acquisition and statistical analysis Scan acquisitions were performed on a 1.5 T scanner, and subsequently images pertaining to each subject were realigned, normalized, and spatially smoothed (Friston et al., 1999). Images were also created for the differences between each condition across L1 and L2 for each subject. Contrast images for each condition and for differences between the respective conditions in L2 and L1 were computed for each subject. Moreover, group effects were computed, using these contrast images by a random-effects analysis in order to be able to generalize the observed effects to the population (Friston et al., 1999). One-sample t-tests were performed separately for each group in order to identify regions within the groups that showed greater activation in L2 than L1 (that is, L1 served as baseline condition in within-group comparisons). Subsequently, two-sample t-tests were performed between groups to highlight regions that were significantly more activated by one group than the other. Results and interpretations While the pattern of brain activity for semantic judgment was largely dependent on PL, AOA mainly affected the cortical representation of grammatical processes (see Figure 3.2 for the brain correlates of grammatical processing in

Figure 3.2 This figure shows the results for grammatical processing of the study of Wartenburger et al. (2003) (see text for details). Results for three groups of bilinguals are displayed: early-acquisition bilinguals (left), late-acquisition and high-proficient bilinguals (middle), and late-acquisition and lowproficient bilinguals (right). The images refer to direct comparisons between L2 and L1 (subtracting L1 from L2 within each group in order to show whether L2 activates a more extended neural system for grammatical processing). As demonstrated, the degree of L2 proficiency does not seem to have strong influences on the pattern of brain activity. The late-acquisition and high-proficient group used the same additional brain activity as the low-proficiency group. Only when L2 was acquired early in life, was the same pattern of brain activity found (left) (modified from Wartenburger et al., 2003). (This figure is published in color at www.psypress.com/ brainscans-etc/)

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a direct comparison between L2 and L1). In detail, in the case of grammar, a comparable performance/proficiency on L1 and L2 was not associated with the same pattern of neural representation. These findings may support the hypothesis that parameters for grammar are set in a “critical period” within the very first years of life, and that this fixation is associated with a distinct pattern of brain activity that is highly specific, and cannot be attained, even in the case of a highly proficient acquisition, later in life. The same did not apply to semantic processing, for which the only difference in the pattern of brain activity appeared to depend on the level of attained proficiency. Thus, these findings support the notion of the existence of a “critical period” of language acquisition and indicate that grammatical processing, given its dependence on age of acquisition, is based on a competence that is neurologically “wiredin”. This experiment is a good example of how neurobiological evidence obtained from functional neuroimaging may enrich linguistic and psycholinguistic debates, yet, as mentioned above, test cognitive theory. Hence, functional imaging techniques may contribute significantly to theories of language representation and language processing.

Concluding remarks A large body of structural and functional neuroimaging studies has been devoted to the investigation of cognitive functions both in the intact human brain and in neurological patients. The studies applying these techniques have not only confirmed the anatomic knowledge gained from neuropsychological lesion studies, but have also opened a number of new perspectives in the understanding of the brain–function relationship. New concepts and methods have led to innovative insights in the understanding of the neurological network underlying neuropsychological functions. New functional neuroimaging methods have shown that the assumption of single, circumscribed localization (lesion-behavior method) for complex and even some basal neuropsychological functions cannot be maintained. For instance, in the case of language processing, most structural imaging studies underline the importance of classical language-related areas within the perisylvian cortex of the left hemisphere, such as Broca’s and Wernicke’s areas. However, functional neuroimaging studies have considerably enlarged and redefined the scope of these areas and their participation in language processing: the left frontal convexity is involved in many tasks, such as word generation (Martin, Wiggs, Ungerleider, & Haxby, 1996), semantic and phonemic fluency (Mummery, Patterson, Hodges, & Wise, 1996; Paulesu et al., 1997), semantic monitoring (Thompson-Schill, D’Esposito, Aguirre, & Farah, 1997), and verbal working memory (Smith, Jonides, & Koeppe, 1996). Moreover, language-related activation has been reported also outside the classical language zone, such as in the inferior temporal gyrus and the temporal pole, the lingual and fusiform gyri (see reviews in Démonet et al., 2005; Indefrey & Levelt, 2000; Price, 2001), the hippocampal formation (Bartha et al., 2005), and even the right cerebellar

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hemisphere (see Mariën, Engelborghs, Fabbro, & De Deyn, 2001). Furthermore, right hemispheric activation in mirror regions is observed during the performance of most language tasks. Functional neuroimaging has brought to the fore that areas related to cognitive processing in the normal human brain appear to be not only more extended, but also less fixed than previously thought. For example, even when the task and experimental design are held constant, changes in languagerelated brain activation can be observed as a consequence of increased familiarity with the task. Striking evidence was provided by Petersen, Van Mier, Fiez, and Raichle (1998), who investigated the effects of practice on a verbal task by PET. The neural differences putatively related to processing differences between a high- and a low-practice performance of verb generation were highlighted by this study, in which decreasing brain activity in the left frontal convexity was reported after practice. Likewise, functional neuroimaging studies have shown that the acquisition of language is achieved through a shift from learning-related activity in the left hippocampus to left perisylvian brain areas (Abutalebi et al., 2007; Opitz & Friederici, 2004). Many challenging breakthroughs in neuropsychology have already been achieved through the advent of functional neuroimaging. Many of the chapters of the present volume show how our basic knowledge significantly increased thanks to these innovative techniques. Further refinement of the methods will help to gain more insight into the healthy human brain and will allow routine application in neurological patients for better diagnosis and treatment.

References Abutalebi, J., Keim, R., Brambati, S. M., Tettamanti, M., Cappa, S. F., De Bleser, R., et al. (2007). Late acquisition of literacy in a native language. Human Brain Mapping, 28, 19–33. Aguirre, G. K., & D’Esposito, M. (1999). Experimental design for brain fMRI. In C.T.W. Moonen & P. A. Bandettini (Eds.), Functional MRI. New York: Springer. Aguirre, G. K., Zarahn, E., & D’Esposito, M. (1998). The variability of human, BOLD hemodynamic responses. NeuroImage, 8, 360–369. Antonini, A., De Notaris, R., Benti, R., De Gaspari, D., & Pezzoli, G. (2001). Perfusion ECD/SPECT in the characterization of cognitive deficits in Parkinson’s disease. Neurological Sciences, 22, 45–46. Bartha, L., Mariën, P., Brenneis, C., Trieb, T., Kremser, C., Ortler, M., et al. (2005). Hippocampal formation involvement in a language activation tasks in patients with mesial temporal lobe epilepsy. Epilepsia, 46, 1754–1763. Basso, A., Lecours, A. R., Moraschini, S., & Vanier, M. (1985). Anatomoclinical correlations of the aphasias as defined through computerized tomography: Exceptions. Brain and Language, 26, 201–229. Berns, G. (1999). Minireview: Functional neuroimaging. Life Sciences, 65, 2531–2540. Bianchi, L. (1895). The functions of the frontal lobes. Brain, 18, 497–522. Birdsong, D. (1999). Second language acquisition and the critical period hypothesis. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.

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Blunk, R., De Bleser, R., Willmes, K., & Zeumer, H. (1981). A refined method to relate morphological and functional aspects of aphasia. European Neurology, 20, 69–79. Bouillaud, J.-B. (1825). Recherches cliniques propres à démontrer que la perte de la parole correspond à la lésion des lobules antérieures du cerveau, et à confirmer l’opinion de M. Gall, sur le siège de l’organe du langage articulé. Archives Générales de Médecine, 8, 25–45. Brissaud, E. (1894). Le rire et le pleurer spasmodiques. Revue Scientifique, 1, 45. Brunner, R. J., Kornhuber, H. H., Seemuller, E., Suger, G., & Wallesch, C. W. (1982). Basal ganglia participation in language pathology. Brain and Language, 16, 281–299. Cappa, S. F., & Vignolo, L. A. (1979). “Transcortical” features of aphasia following left thalamic hemorrhage. Cortex, 15, 121–130. Cappa, S. F., De Fanti, C. A., De Marco, R., Magni, E., Messa, C., & Fazio, F. (1993). Progressive dysphasic dementia with bucco-facial apraxia: A case report. Behavioural Neurology, 6, 159–163. Chetelat, G., & Baron, J. C. (2003). Early diagnosis of Alzheimer’s disease: Contribution of structural neuroimaging. NeuroImage, 18, 525–541. Clements, A. M., Rimrodt, S. L., Abel, J. R., Blankner, J. G., Mostofsky, S. H., Pekar, J. J., et al. (2006). Sex differences in cerebral laterality of language and visuospatial processing. Brain and Language, 98, 150–158. Dale, A. M., & Buckner, R. L. (1997). Selective averaging of rapidly presented individual trials using fMRI. Human Brain Mapping, 5, 329–340. Damasio, A. R., Damasio, H., Rizzo, M., Varney, N., & Gersh, F. (1982). Aphasia with nonhemorrhagic lesions in the basal ganglia and internal capsule. Archives of Neurology, 39, 15–20. Damasio, H., Damasio, A., Hamsher, K., & Varney, N. (1979). CT scan correlates of aphasia and allied disorders. Neurology, 29, 572. Damasio, H., & Damasio, A. R. (1980). The anatomoclinical basis of conduction aphasia. Brain, 103, 337–350. Damasio, H., & Damasio, A. R. (1989). Lesion analysis in neuropsychology. New York: Oxford University Press. Déjerine, J. (1892). Contribution à l’étude anatomo-pathologique et clinique des différentes variétés de cécité verbale. Mémoires de la Société de Biologie, 4, 61–90. Démonet, J. F., Pernet, C., Kouider, S., & Musso, M. (2005). The dynamics of language-related brain images. Neurocase, 11, 148–150. De Renzi, E., Perani, D., Carlesimo, G. A., Silveri, M. C., & Fazio, F. (1994). Prosopagnosia can be associated with damage confined to the right hemisphere: An MRI and PET study and a review of the literature. Neuropsychologia, 32, 893–902. Fox, P., & Raichle, M. (1986). Focal physiological uncoupling of cerebral blood flow and oxidative metabolism during somatosensory stimulation in human subjects. Proceedings of the National Academy of Sciences of the USA, 83, 1140–1144. Freud, S. (1891). Zur Auffassung der Aphasien. Leipzig und Wien: Deuticke. Friston, K., Price, C. J., Fletcher, P., Moore, C., Frackowiak, R. S. J., & Dolan, R. J. (1996). The trouble with cognitive subtraction. NeuroImage, 4, 97–104. Friston, K. J., Holmes, A. P., Price, C. J., Buchel, C., & Worsley, K. J. (1999). Multisubject fMRI studies and conjunction analyses. NeuroImage, 10, 385–396. Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J. P., Frith, C. D., & Frackowiak, R. S. J. (1995). Statistical parametric maps in functional imaging: A general linear approach. Human Brain Mapping, 2, 189–210.

70

Abutalebi et al.

Gizewski, E. R., Krause, E., Wanke, I., Forsting, M., & Senf, W. (2006). Genderspecific cerebral activation during cognitive tasks using functional MRI: Comparison of women in mid-luteal phase and men. Neuroradiology, 48, 14–20. Hayward, R. W., Naeser, M. A., & Zatz, L. M. (1977). Cranial computed tomography in aphasia. Radiology, 123, 653–660. Hoffmann, H. (1885). Stereognostische Versuche. Deutsches Archiv für Klinische Medizin, 36, 398–426. Hughlings Jackson, J. (1878). On affections of speech from disease of the brain. Brain, 1, 304–330. Indefrey, P., & Levelt, W. J. M. (2000). The neural correlates of language production. In M. S. Gazzaniga (Ed.), The new cognitive neurosciences. Cambridge, MA: MIT Press. James, W. (1890). Principles of psychology. New York: Holt. Johnson, J., & Newport, E. (1989). Critical period effects in second language learning: The influence of maturational state on the acquisition of English as a second language. Cognitive Psychology, 21, 60–99. Kertesz, A., Harlock, W., & Coates, R. (1979). Computer tomographic localization lesion size, and prognosis in aphasia and nonverbal impairment. Brain and Language, 8, 34–50. Kim, K. H. S., Relkin, N. R., Lee, K. M., & Hirsch, J. (1997). Distinct cortical areas associated with native and second languages. Nature, 388, 171–174. Kroll, J. F., & Stewart, E. (1994). Category interference in translation and picture naming: Evidence for asymmetric connections between bilingual memory representations. Journal of Language and Memory, 33, 149–174. Lenneberg, E. H. (1967). Biological foundations of language. New York: Wiley. Liepmann, H. (1900). Das Krankheitsbild der Apraxie (motorischen Asymbolie). Monatsschrift für Psychiatrie und Neurologie, 8, 15–44. Mariën, P., Engelborghs, S., Fabbro, F., & De Deyn, P.P. (2001). The lateralized linguistic cerebellum: A review and new hypothesis. Brain and Language, 79, 580–600. Martin, A., Wiggs, C. L., Ungerleider, L. G., & Haxby, E. (1996). Neural correlates of category-specific knowledge. Nature, 379, 649–652. Mayes, A. R., & Montaldi, D. (2001). Exploring the neural bases of episodic and semantic memory: The role of structural and functional neuroimaging. Neuroscience and Biobehavioral Review, 25, 555–573. Mazzocchi, F., & Vignolo, L. A. (1979). Localisation of lesions in aphasia: ClinicalC.T. scan correlations in stroke patients. Cortex, 15, 627–654. Mohr, J. P. (1983). Thalamic lesions and syndromes. In A. Kertesz (Ed.), Localization in neuropsychology (pp. 269–293). New York: Academic Press. Moro, A., Tettamanti, M., Perani, D., Donati, C., Cappa, S. F., & Fazio, F. (2001). Syntax and the brain: Disentangling grammar by selective anomalies. NeuroImage, 13, 110–118. Mosso, A. (1881). Über den Kreislauf des Blutes im menschlichen Gehirn. Leipzig: Viet. Mummery, C. J., Patterson, K., Hodges, J. R., & Wise, R. J. S. (1996). Generating a “tiger” as an animal name or a word beginning with T: Differences in brain activations. Proceedings of the Royal Society of London. Series B, Biological Sciences, 263, 989–995. Munk, H. (1878). Weitere Mitteilungen zur Physiologie der Grosshirnrinde. Archiv für Anatomie und Physiologie, 2, 162–178.

3. Structural and functional neuroimaging

71

Murdoch, B. E., Afford, R. J., Ling, A. R., & Ganguley, B. (1986). Acute computerized tomographic scans: Their value in the localization of lesions and as prognostic indicators in aphasia. Journal of Communication Disorders, 19, 311–345. Naeser, M. A. (1983). CT scan lesion size and lesion locus in cortical and subcortical aphasia. In A. Kertesz (Ed.), Localization in neuropsychology (pp. 63–119). New York: Academic Press. Naeser, M. A., & Hayward, R. W. (1978). Lesion localization in aphasia with cranial computed tomography and the Boston Diagnostic Aphasia Exam. Neurology, 28, 545–551. Neville, H. J., & Bavelier, D. (1998). Neural organization and plasticity of language. Current Opinion in Neurobiology, 8, 254–258. Noel, G., Collard, M., Dupont, H., & Huvelle, R. (1977). Nouvelles possibilités de corrélations anatomocliniques en aphasiologie grâce à la tomodensitométrie cérébrale. Acta Neurologica Belgica, 77, 351–362. Oitres, A. (1895). Étude sur l’aphasie chez les polyglottes. Revue de Médecine, 15, 873–899. Opitz, B., & Friederici, A. D. (2004). Interactions of the hippocampal system and the prefrontal cortex in learning language-like rules. NeuroImage, 19, 1730– 1737. Paulesu, E., Goldacre, B., Scifo, P., Cappa, S. F., Gilardi, M. C., Castiglioni, I., et al. (1997). Functional heterogeneity of left inferior frontal cortex as revealed by fMRI. Neuroreport, 28, 2011–2017. Perani, D., & Abutalebi, J. (2005). Neural basis of first and second language processing. Current Opinion in Neurobiology, 15, 202–206. Perani, D., Abutalebi, J., Paulesu, E., Brambati, S., Scifo, P., Cappa, S. F., et al. (2003). The role of age of acquisition and language usage in early, high-proficient bilinguals: A fMRI study during verbal fluency. Human Brain Mapping, 19, 179–182. Perani, D., Di Piero, V., Vallar, G., Cappa, S., Messa, C., Bottini, A., et al. (1988a). Technetium 99m HM-Pao SPECT study of regional cerebral perfusion in early Alzheimer’s disease. Journal of Nuclear Medicine, 29, 1507–1515. Perani, D., Papagno, C., Cappa, S. F., Gerundini, P., & Fazio F. (1988b). Crossed aphasia: Studies with single photon emission computerized tomography. Cortex, 24, 171–178. Petersen, S. E., Van Mier, H., Fiez, J. A., & Raichle, M. E. (1998). The effects of practice on the functional anatomy of task performance. Proceedings of the National Academy of Sciences of the USA, 95, 853–860. Pitres, A. (1895). Étude sur l’aphasie chez les polyglottes. Revue de Médecine, 15, 873–899. Pitres, A. (1898). L’Aphasie Amnésique et ses variétés cliniques. Paris: Alcan. Price, C. J. (2001). The anatomy of language: Contributions from functional neuroimaging. Journal of Anatomy, 197, 335–359. Reinvang, I., & Dugstad, G. (1981). Aphasia typology and lesion localization with computed axial tomography. Scandinavian Journal of Rehabilitation Medicine, 13, 85–88. Savoy, R. L., Bandettini, P. A., O’Craven, K. M., Kwong, K. K., Davis, T. L., Baker, J. R., et al. (1996). Detection of cortical activation during averaged single trials of a cognitive task using functional magnetic resonance imaging. Proceedings of the National Academy of Sciences of the USA, 93, 14878–14883.

72

Abutalebi et al.

Smith, E. E., Jonides, J., & Koeppe, R. A. (1996). Dissociating verbal and spatial working memory using PET. Cerebral Cortex, 6, 11–20. Sokoloff, L. (1975). Possible role of cerebral ketone body metabolism in diabetic coma. In D. H. Ingvar and N. A. Lassen (Eds.), Brain work: The coupling of function, metabolism, and blood flow in the brain (pp. 336–339). Copenhagen: Munksgaard. Strauss, H. (1924). Über konstruktive Apraxie. Monatsschrift für Psychiatrie und Neurologie, 56, 65–124. Thompson-Schill, S. L., D’Esposito, M., Aguirre, G. K., & Farah, M. J. (1997). Role of left inferior prefrontal cortex in retrieval of semantic knowledge: A reevaluation. Proceedings of the National Academy of Sciences of the USA, 94, 14792–14797. Wartenburger, I., Heekeren, H. R., Abutalebi, J., Cappa, S. F., Villringer, A., & Perani, D. (2003). Early setting of grammatical processing in the bilingual brain. Neuron, 37, 159–170. Wernicke, C. (1874). Der aphasische Symptomencomplex. Breslau: Cohn und Weigert. Wernicke, C. (1895). Zwei Fälle von Rindenläsion. Arbeiten aus dem klinischen Psychiatrie Breslau, 2, 33–53. Yarnell, P., Monroe, M. A., & Sobel, L. (1976). Aphasia outcome in stroke: A clinical and neurological correlation. Stroke, 7, 516–522.

SECTION II

Language disorders

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Information-processing models of aphasia Updating the diagram makers Kenneth M. Heilman

Aphasia is a common, disabling cognitive deficit. The purpose of this chapter is to discuss the aphasic syndromes, using both a historic and cognitive, information-processing-diagrammatic, modeling approach. Much of this chapter is an updated version of a previously published paper (Heilman, 2006). It is hoped that this approach may have heuristic value and will allow people to understand as well as investigate the neuropsychological mechanisms that lead to aphasic disorders as well as the rationale for testing, therapy, and management. It is also hoped that this information-processing approach will help us gain understanding of the means by which the normal human brain processes speech and language.

Gall and Broca Broca’s aphasia The localizationist concept that the brain is organized in a modular fashion dates back to the early part of the nineteenth century when Franz Joseph Gall proposed that specific areas of the brain are important for mediating different cognitive functions. Unfortunately, this localizing hypothesis, together with his postulate that bigger is better, led to the pseudoscience of phrenology, whose followers believed that by palpating and measuring the skull a phrenologist could determine a person’s mental abilities. Although phrenology had been discredited, the postulate of localized function—or what is now termed modularity—was widely discussed in nineteenth-century Europe. Paul Broca, a French physician-surgeon and anthropologist, was strongly influenced by the lectures and discussions of Auburtin, who, along with his father-in-law Bouillaud (a student of Gall), believed that speech is mediated by the frontal lobes. According to Head (1926), Auburtin’s belief in this localization of speech was so strong that he offered to recant his faith in Gall’s localization doctrine if anyone could show him a patient with a loss of speech not associated with a lesion of the frontal lobes. In reaction to Auburtin’s statement, Paul Broca invited Auburtin to his hospital to see Leborgne, a patient who was recently admitted to the hospital because of

76 Heilman cellulitis of his leg, but Leborgne had a history of a stroke that induced speech loss and right hemiplegia. At the hospital, the patient was known as “Tan”, because this was the only word he could utter. When Auburtin saw this case with Broca, he agreed that the patient had a loss of speech and should have a lesion of the anterior lobes of the brain. Broca noted that although Tan was unable to speak or write, he was able to understand spoken language. About 6 days later, the patient died and a postmortem examination revealed a discrete lesion—approximately the size of an egg—in the left hemisphere. This lesion included inferior portions of the frontal lobe, portions of the insula, corpus striatum and the anterior superior temporal lobe. Broca presented this patient’s brain to members of the French Anthropology Society, citing this case as support for the localizationist postulates of Gall, Bouillaud, and Auburtin. According to Broca, the inability of this patient to speak was caused by a disorder of the special faculty of articulated language mediated by the frontal lobe. Broca termed this speech disorder aphemia. Subsequently, he observed another patient with a fractured femur who also suffered from aphemia. On postmortem examination, this patient also exhibited a lesion of the second and third frontal convolutions, providing further evidence for Gall’s localizationist postulate. Broca’s reports had a dramatic influence on thinking in Europe, including England, where he lectured and presented his findings. In 1864, Trousseau learned from a Greek physician that Broca’s term aphemia meant “infamous” and therefore suggested the term aphasia. Broca’s aphasia is now a well-recognized disorder. Patients with Broca’s aphasia present with a phonetic disintegration of speech (Alajouanine, Ombredane, & Durand (1939), whereas speech comprehension is relatively spared. Consequently, their speech is characterized by reduced fluency with frequent phonological errors. Patients with this type of aphasia demonstrate syntactic disorders in both expression and comprehension. Naming and repetition may be disturbed as well. Mohr, Pessin, Finkelstein, Funkenstein, Duncan, and Davis (1978) demonstrated that when patients’ lesions are confined to the inferior frontal operculum, including the pars triangularis and opercularis, their speech impairment is usually only temporary and that a larger lesion, involving the motor and insular cortex, as well as subcortical structures such as the basal ganglia, might be important in persistent aphasia. The observation that lesions restricted to the frontal operculum might not cause a persistent speech disorder does not, however, contradict Broca’s localization of this disorder but rather suggests that other areas may be able to compensate for the injured areas. Broca (1861) also observed several other patients that had a right-hand preference and aphasia associated with right hemiplegia. Based on these observations, Broca concluded that in people who prefer their right hand, speech is primarily mediated by the left hemisphere. These reports by Broca provided strong evidence that the human brain is organized in modular

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fashion, as Gall predicted, and subsequent studies of Broca’s area have also demonstrated that in patients who are left hemisphere dominant for speech, the Broca’s area on the left is larger than that on the right (Foundas et al., 1998), supporting Gall’s second postulate that bigger is better.

Wernicke’s information-processing model Wernicke’s aphasia Broca’s reports were probably the impetus for the increased interest in neuroanatomy that occurred in the second half of the nineteenth century. Meynert demonstrated that sensory input to the cerebral cortex predominantly projects to the posterior portions of the cortex, whereas the neuronal networks that control efferent-motor output are mainly anterior. Accordingly, Broca’s aphasia would be considered primarily an efferent disorder. In 1874, Carl Wernicke, one of Meynert’s students, wrote Der aphasische Symptomencomplex, probably the most influential paper on aphasia. In this paper, Wernicke contrasted Broca’s (motor) aphasia with a sensory type of aphasia that is currently called Wernicke’s aphasia. Unlike patients with Broca’s aphasia, who are nonfluent, patients with sensory aphasia are fluent. Some patients are so fluent that their speech may be characterized as logorrhea. These patients’ spontaneous speech contains not only phonological and semantic errors but also many pseudowords or nonwords, also called neologisms. Furthermore, the speech of patients with Wernicke’s aphasia may be entirely comprised of neologisms such that they may sound as if they are speaking a foreign language. Unlike patients with Broca’s aphasia, who can understand speech that does not exceed their working memory or syntactic abilities, patients with Wernicke’s aphasia suffer from a severe comprehension disorder. They also have naming and repetition deficits. Whereas patients with Broca’s aphasia have anterior perisylvian lesions, patients with Wernicke’s aphasia have posterior perisylvian lesions. Wernicke suggested that the critical area might be the posterior portion of the superior temporal lobe, a portion of the auditory association cortex. Wernicke stated that patients with sensory aphasia have lost the memory of how words sound. In the absence of this information store, now called the phonological lexicon, the words heard by these patients sound like a foreign language that they never learned. When attempting to name an object, they are unable to recall the set of speech sounds or phonemes that represent this object. They also have this same problem when attempting to speak spontaneously, being unable to activate the word representations that symbolize or express their thoughts. In patients with lesions restricted to Wernicke’s area, Broca’s area remains intact and able to produce phoneme sequences. As a result, these patients can speak, but the words used are not constrained by phonological-lexical knowledge. Consequently, these patients’ speech disorder is also often called jargon aphasia.

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In Wernicke’s classical paper, not only did he suggest a second speechlanguage module, but he was also the first to introduce an informationprocessing network when he suggested that the area that contains the memories of how words sound (the phonological lexicon or Wernicke’s area) provides information to other areas of the brain where the sounds that comprise these words are programmed (Broca’s area). Consequently, according to Wernicke, the posterior portion of the superior temporal gyrus must be anatomically connected to Broca’s area in the frontal operculum. Conduction aphasia In accord with his information-processing system (Figure 4.1), Wernicke further posited that if this connection between Broca’s area and the posterior portion of the superior temporal gyrus were disconnected by a lesion, the patient would also be aphasic. Since the phonological lexicon cannot entirely inform Broca’s area about the sound ( phonemic) composition of words, the production of words is impaired, resulting in phonological errors and neologisms. However, unlike the patients with sensory (Wernicke’s) aphasia who cannot monitor their errors, due to destruction of their phonological lexicon, patients with this disconnection disorder are able to monitor their errors and may attempt to correct them. In Wernicke’s hypothetical form of aphasia, the phonological lexicon has been disconnected from Broca’s area; therefore, according to this information-processing model, these patients should also

Figure 4.1 Wernicke’s model. A = pure word deafness (impaired comprehension and repetition, intact spontaneous speech, naming, and reading); B = Wernicke’s aphasia (fluent jargon with multiple phonemic errors, impaired comprehension, repetition, and naming); C = conduction aphasia (fluent with phonemic, paraphasic errors, impaired repetition, naming, and intact comprehension); D = Broca’s aphasia (nonfluent, impaired naming and repetition, and intact comprehension of major lexical items).

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have problems with repetition and naming. However, because they maintain an intact phonological lexicon, stored in the posterior portion of the superior temporal gyrus, they should be able to comprehend speech. After Wernicke suggested this new form of aphasia, patients who demonstrated this constellation of symptoms were reported, and the term currently used for this aphasic syndrome is conduction aphasia. Pure word deafness Bastian (1869) and Kussmaul (1877) described patients who were unable to comprehend speech or to repeat but who could name things and speak normally. As mentioned above, Meynert demonstrated that auditory input from the thalamus projects to the primary auditory cortex situated on the dorsal surface of the superior temporal gyrus. In addition to this, Wernicke posited that sensory aphasia is caused by a lesion of the auditory association cortex posterior to this primary auditory cortex. In accord with the information-processing model of Wernicke, the disorder described by Bastian (1869) and Kussmaul (1877), now called pure word deafness, is thought to be related to the inability of auditory information to access an intact Wernicke’s area.

Head’s diatribe against the “diagram makers” Although one of Wernicke’s most important contributions was the development of information-processing models, Henry Head (1926) dismissed both Wernicke and other investigators who used this information-processing approach as “diagram makers”. Head believed that the reports of these “diagram makers” were biased or even untruthful. For example, referring to Wernicke’s report, Head (1926) wrote, “No better example could be chosen of the manner in which the writers of this period were compelled to lop and twist their cases to fit the Procrustean bed of their hypotheses.” Instead of detracting from these early diagram makers’ observations, subsequent reports, by other clinicians, replicated these diagram makers’ clinical observations. In addition, the information-processing model approach first put forth by Wernicke and the other early diagram makers has been demonstrated to have strong heuristic value. Just as it helped Wernicke to predict conduction aphasia, the information-processing model may allow one to develop hypotheses about how the brain works and what type of dysfunction may be encountered with various brain lesions. In spite of Henry Head’s diatribe and admonitions, in the past three to four decades, there has been a renewed interest in using information-processing models to help explain cognitive deficits associated with aphasia and to develop new a priori hypotheses.

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Lichtheim’s model Eleven years after Wernicke’s influential report, a third landmark paper was written by Lichtheim (1885). In this paper, he reviewed the seminal contributions of Paul Broca (1861) and Carl Wernicke (1874) and proposed modifications to Wernicke’s schema (Figure 4.2). This new information-processing model or schema contained Wernicke’s arc, which includes the following: the primary auditory cortex, which performs the auditory analysis of the incoming auditory signals; the posterior superior temporal gyrus (Wernicke’s area), which stores memories of how words sound (now called the phonological lexicon); connections from Wernicke’s area to the anterior perisylvian region (Broca’s area), where word sounds are programmed (phonetic programmer); and projections from Broca’s area to the regions of the primary motor cortex that control the articulatory apparatus. According to Lichtheim, in addition to Wernicke’s arc, the speech cortex contains a region where concepts are elaborated: the conceptual or semantic field. Before describing the cases that Lichtheim thought would support this model, he explained how this system worked. According to Lichtheim, after auditory analysis, speech input is processed by Wernicke’s area (the phonological lexicon), where the representations of word sounds are activated.

Figure 4.2 Lichtheim’s modification of Wernicke’s model. Dysfunction at A, B, C, D, E, and F; see Figure 4.1. G or H = transcortical sensory aphasia; I = transcortical motor aphasia; G, H, and I = mixed transcortical aphasia.

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After phonological lexical activation, this information is transmitted to the area where concepts are elaborated (conceptual-semantic field). Repetition would take place as Wernicke has posited, via auditory analysis, phonological-lexical activation, and transmission of this lexical information through the arcuate fasciculus with activation of the motor-phonetic representations. These motor speech representations then activate the motor cortex. According to Lichtheim, spontaneous speech starts with activating concepts, which, in turn, activate the motor representations of speech sounds and then the motor cortex. According to Lichtheim’s model, and as suggested by Bastian and Kussmaul, a lesion that prevents auditory information from reaching the phonological lexicon would impair comprehension and repetition. Spontaneous speech, however, would be normal. As discussed above, this disorder has been termed pure word deafness. As demonstrated by Wernicke, damage to the phonological lexicon would produce Wernicke’s aphasia since word sound knowledge is important for verbal comprehension, spontaneous speech, naming, and repetition. Conduction aphasia with impaired repetition can be explained by disconnection between the phonological lexical representations, which contain word sound knowledge, and the phonetic motor representations, important in providing the articulatory programs to the motor cortex. This disconnection would not impair comprehension, since the lexical representations can still get access to the region where concepts are elaborated. Destruction of the motor phonetic representation of speech (Broca’s aphasia) would also not impair comprehension because word sounds ( phonological lexicon) can still access concepts, but would impair spontaneous speech, naming, and repetition because the phonetic-articulatory representations would not be available to program the motor cortex. Transcortical sensory aphasia From Lichtheim’s schema, two additional types of aphasic syndromes can be identified. If there is a functional disconnection between the phonological lexicon and the conceptual-semantic field, patients should not be able to comprehend, but, unlike patients with Wernicke’s aphasia, they should be able to repeat because Wernicke’s arc remains intact. To support his postulate, Lichtheim described a 60-year-old man who had impaired ability to understand but preserved ability to repeat; this now is a well-known syndrome called transcortical sensory aphasia. Transcortical motor aphasia Lichtheim’s schema also suggests that interruption between the area of concepts and motor phonetic representations should also produce nonfluent aphasia, which would be unlike Broca’s aphasia, because these patients should have normal repetition and should not make frequent phonological

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paraphasic errors, but, as in Broca’s aphasia, they would have relatively spared comprehension. Lichtheim provided evidence for the existence of this type of aphasia by presenting a patient who, after a carriage accident, could say only “yes” or “no”. Although this patient was nonfluent, he was able to comprehend well. Unlike patients with Broca’s aphasia, this patient, even early in the course of his disease, was able to repeat flawlessly. This disorder is known as transcortical motor aphasia.

Kussmaul’s model About 8 years before Lichtheim reported a patient with transcortical sensory aphasia, as well as his alteration of Wernicke’s model to account for this patient’s signs, Kussmaul (1877) also reported a patient who had impaired comprehension with intact repetition, and Kussmaul also posited an information-processing model similar to Lichtheim’s model. Kussmaul’s schema, however, differed from Lichtheim’s in that the area of concepts could gain access to the phonetic motor representations only via the phonological lexicon (Figure 4.3). After an experiment with a patient with Broca’s aphasia, however, Lichtheim rejected Kussmaul’s model. Lichtheim showed this patient objects and asked him to indicate by squeezing his hand the number of syllables of the word that denoted this object. He found that Broca’s aphasia patients could not adequately perform this task. According to Lichtheim’s model (Figure 4.2), conceptual representations cannot directly access the phonological lexicon. Therefore, after the object is seen and the area of concepts is activated, motor speech (phonetic) representations are activated in concert with activation of the phonological lexical representations. In Broca’s aphasia, the motor speech (phonetic) representations are degraded and, according to Lichtheim, patients are unable to detect how many syllables a word contains since they cannot access the phonological lexicon. In Kussmaul’s model, the seen objects activate the semantic conceptual representations, and these concept representations directly access the phonological lexicon. Therefore, according to Kussmaul’s model, patients with destruction of the motor speech ( phonetic) representations should have no difficulty in accessing the information stored in the phonological lexicon. Since the patients with Broca’s aphasia examined by Lichtheim appeared to be impaired at accessing the lexicon, he rejected Kussmaul’s model. According to Lichtheim’s model, when patients with Broca’s or conduction aphasia are presented with pairs of objects and have to determine whether the names of the two objects are phonologically identical (homophones versus nonhomophones), they should fail to do so. They should be impaired in this homophone test because lesions in Broca’s area or its connections to Wernicke’s area ( phonological lexicon) should prevent the conceptual field from accessing the phonological lexicon where word sounds are stored. Feinberg, Gonzalez-Rothi, and Heilman (1986), however, demonstrated that

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Figure 4.3 Kussmaul’s model. Dysfunction at E together with G and/or F induces the signs of transcortical aphasia, in which patients have impaired comprehension and naming, fluent but empty speech, and intact repetition. Unlike the patients with transcortical aphasia from dysfunction at F, patients with dysfunction (dissociation) at E and G have evidence of intact semanticconceptual representations. Patients with dysfunction at G have anomic aphasia, and those with dysfunction at E have transcortical aphasia with intact naming and speech.

patients with conduction aphasia can successfully perform homophone judgments on words that they cannot vocalize. The evidence that these patients can access their phonological lexicons argues against Lichtheim’s suggestion that semantic-conceptual representations access the phonological lexicon through Broca’s area, and instead appears to support Kussmaul’s model. Lichtheim’s model has two other possible flaws. According to this model, patients with a disconnection between the phonological lexicon and the area of concepts should be impaired in comprehending speech but should be able to repeat, just as he demonstrated in his case report of the patient with transcortical sensory aphasia. However, a detailed review of this case revealed that this patient used incorrect words and occasionally mutilated words. He also had problems with naming. According to Lichtheim’s model, the area of concepts has direct access to motor speech (phonetic) representations, and the motor representations can access the phonological lexicon. Since these three areas are intact and interconnected, this patient should have

84 Heilman had normal spontaneous speech and should have been able to name, but he was impaired. Anomic aphasia Lichtheim’s model cannot account for the patient with anomic aphasia whose word finding is impaired when speaking spontaneously and when attempting to name objects and actions that are presented visually or in other modalities (confrontation naming), but who has normal speech comprehension and repetition. Lichtheim was aware that his model could not account for anomic aphasia. He considered that the interruption of the pathway between the area of concepts and motor speech ( phonetic) representations could theoretically produce a defect in naming, but he had already stated that this defect causes decreased fluency with intact repetition (transcortical motor aphasia). Since Lichtheim realized that his model could not account for anomic aphasia, he tried to dispense with anomia as a specific aphasic subtype: “It seems to me questionable, however, to place amnesia [anomic aphasia] on a par with the other phenomena of aphasic disturbance.” Lichtheim was partly correct when he noted that anomia is often a residual of many different forms of aphasia, but it has also been clearly demonstrated that anomia, in isolation, can occur after a discrete lesion. Whereas patients with deficits in the semantic-conceptual field or in the phonological lexicon may be impaired in naming, patients with transcortical sensory aphasia and Wernicke’s aphasia have comprehension and repetition deficits. The patient with true isolated anomic aphasia displays normal comprehension and normal repetition. Unlike Lichtheim’s model, Kussmaul’s model contains reciprocal pathways from the phonological lexicon to the area of concepts or semantics, and from the area of concepts to the lexicon. A functional disconnection between semantics and the phonological lexicon in Kussmaul’s model may be the best explanation of pure anomic aphasia. Transcortical aphasia with intact naming This explanation of anomic aphasia, which is based on Kussmaul’s model, of Wernicke’s model, presumes that a patient can have a one-way disconnection or dissociation between the conceptual-semantic field and the phonological lexicon. If anomic aphasia is caused by the inability of the semantic field to access the lexicon with a preserved ability of the lexicon to access the semantic field, it should be possible to observe the occurrence of the opposite oneway dissociation. Heilman, Tucker, and Valenstein (1976) reported a patient with mixed transcortical aphasia who was nonfluent and had impaired comprehension but did have intact repetition and naming (mixed transcortical aphasia with intact naming). In addition, Heilman, Gonzalez-Rothi, McFarling, and Rottman (1981) reported a patient who had impaired comprehension, but intact repetition, naming, and spontaneous speech (transcortical

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sensory aphasia with intact naming and speech). These patients’ profiles suggest a one-way dissociation, such that the phonological lexicon cannot access the semantic-conceptual representations, but these conceptual-semantic representations can access the phonological lexicon.

Modified Wernicke–Kussmaul–Lichtheim model The transcortical motor aphasias: adynamic aphasia, speech akinesia, and spontaneous speech anomia Kussmaul’s model, unlike Lichtheim’s, can explain almost all the traditional aphasic syndromes, including transcortical sensory aphasia (impaired comprehension, naming, and spontaneous speech with intact repetition), as a functional disconnection between the phonological lexicon (Wernicke’s area) and the conceptual-semantic field or a destruction of the conceptual-semantic representations. Kussmaul’s model also can account for other disorders such as pure anomic aphasia and transcortical sensory aphasia with intact naming and speech. However, this model cannot account for transcortical motor aphasia, in which patients have nonfluent speech with normal comprehension and repetition. When patients have transcortical motor aphasia, their brain injuries are most commonly in the medial and dorsolateral frontal lobe (superior to Broca’s area) in addition to subcortical lesions (as in the medial thalamus). The medial and dorsolateral frontal lobe, including the anterior cingulate gyrus together with the basal ganglia and thalamus, forms what we have termed an intentional system. As described by Nielsen (1951), bilateral damage to these areas is associated with akinetic mutism, and it appears that lesions to these areas that are restricted to the left side are associated with transcortical motor aphasia (Rubens, 1975). There appear to be three different types of transcortical motor aphasia. The first type is characterized by inability to activate the semantic-conceptual network (adynamic aphasia), and the second type by deficit of motor speech activation (speech akinesia or extrasylvian motor aphasia type II of Benson). Recently, we have observed what might be a third type that we call “spontaneous speech anomia”. Nonfluency is the major sign of all three of these disorders, but, unlike patients with Broca’s aphasia, patients with all these forms of transcortical motor aphasia show normal repetition. Whereas patients with adynamic aphasia may be mildly impaired at naming to confrontation, those with speech akinesia and spontaneous speech anomia name normally or almost normally when presented with objects and asked to name them. Patients with spontaneous speech anomia have difficulty in word finding when attempting to speak spontaneously, but those with akinesia of speech have little or nothing to say. These three forms of aphasia with reduced fluency and intact repetition might be best distinguished by different forms of fluency testing. Patients with adynamic aphasia have a greater decrease in fluency when performing the

86 Heilman category fluency tests (in 1 minute, name as many different animals as you can) than when performing the letter-phoneme fluency test (name as many words that begin with the letter f as you can in 1 minute). In contrast, patients with spontaneous speech anomia are more impaired with letter-phoneme fluency than category fluency. Patients with speech akinesia have a severe reduction of fluency with both tests and often show a dramatic reduction of output in the second 30 s of these fluency tests (cognitive impersistence). Benson and Ardila (1996) suggest that adynamic aphasia is associated with dorsolateral frontal lesions (superior to Broca’s area), whereas speech akinesia is more frequently observed in patients with medial frontal lesions. The patients that we have seen with spontaneous speech anomia appear to have early semantic dementia, a form of frontal-temporal lobar degeneration that is most often associated with left anterior temporal lobe atrophy. Our modification of the Wernicke–Kussmaul–Lichtheim model is illustrated in Figure 4.4. As indicated by this diagram, damage to the intentional system and its interactions with the output lexicon induces spontaneous speech anomia with impaired letter-phoneme fluency. In contrast, damage to the intentional system and its interaction with semantics induces adynamic aphasia with impaired category fluency, and damage to the intentional system and its connection with the motor speech areas causes akinesia of speech. Deep dysphasia There is an additional problem with both the Lichtheim (Figure 4.2) and Kussmaul (Figure 4.3) models. Several investigators have described a rare aphasic disorder called deep dysphasia (Katz & Goodglass, 1990). These patients’ speech strongly resembles that of patients with conduction aphasia. However, unlike patients with classic conduction aphasia, who primarily produce phonological errors when attempting to repeat, these patients make semantic errors, saying good, well-formed words, but not the correct words. In addition, patients with deep dysphasia cannot repeat nonwords. Although none of the models we discussed above can explain this syndrome, a further modification of the Wernicke–Lichtheim–Kussmaul’s model can account for deep dysphasia. There is some evidence that the phonological lexicon might be composed of two separate but connected modules, a phonological input lexicon that is important in word recognition and a phonological output lexicon important in word production (Figure 4.4). This separation of the input and output phonological lexicons may explain the two different forms of conduction aphasia. One form may be caused by a functional dissociation between the phonological input and output lexicons. The second form may be caused by a degradation of the phonological output lexicon or a functional dissociation between the phonological output lexicon and Broca’s area. According to our modification of the Wernicke–Kussmaul–Lichtheim model, the degradation

Figure 4.4 Modified Wernicke–Kussmaul–Lichtheim schema. Locus of dysfunction. A = pure word deafness ( patients can spontaneously speak and name, but cannot understand speech or repeat speech). B, C, and D = Wernicke’s aphasia (patients are fluent, make phonological errors and neologisms, and have impaired comprehension, repetition, and naming). D, and E = conduction aphasia (patients are fluent but make phonological errors; they can comprehend (A, B, H, and I), but cannot normally repeat or name). C = deep dysphasia (this disorder is similar to conduction aphasia except patients make semantic errors and cannot repeat nonwords; patients repeat by pathway A, B, H, I, M, D, E, F, and G). F = Broca’s aphasia (nonfluent, phonemic errors, impaired repetition, and naming but intact comprehension (A, B, H, and I). I = transcortical sensory aphasia (patients have semantic jargon output (D, E, F, and G) and cannot comprehend or name, but can repeat (A, B, C, D, E, F, and G). G = aphemia ( patients are nonfluent, and impaired at repetition and naming, but can comprehend and write). M = anomic aphasia ( patients are fluent with circumlocution, impaired naming with intact repetition (A, B, C, D, E, F, and G), and comprehension (A, B, H, and I); patients name and speak by using pathway I, Q, and F). N = optic aphasia ( patients are impaired at naming visually presented object, but can describe objects via pathway L, K, I, M, D, E, F, and G; patents can also comprehend (A, B, H, and I), repeat (A, B, C, D, E, F, and G) and speak normally (L, M, D, E, F, and G)). K and I = nonoptic aphasia ( patients name objects by pathway L, N, D, E, and F, but cannot name to definition because of degradation of the semantic field). J = adynamic aphasia ( patients do not initiate speech or carry on a conversation, but can understand speech, repeat, and name); patients with milder defects in the system might have reduced semantic-category fluency, but have normal or better letter-phoneme fluency (e.g. Controlled Oral Word Association test). O = speech akinesia (not an aphasic disorder; patients might be hypophonic and have palillia). P = patients with disorder might not appear aphasic, but are impaired in letter-phoneme fluency test (Controlled Oral Word Fluency Test).

88 Heilman of the phonological output lexicon or a functional disconnection between the phonological output lexicon and Broca’s area causes the traditional type of conduction aphasia, in which lexical (word)-phonological information has a reduced influence on Broca’s area, which is important in the selection of the phonetic sequence programs used in speech. Thus, patients with this traditional form of conduction aphasia make phonological paraphasic errors when repeating, naming, and speaking spontaneously. In contrast, when patients with a functional disconnection between the phonological input and output lexicons attempt to repeat, since their input lexicon cannot directly access their output lexicon, they might attempt to use an alternative route. According to the modified Wernicke–Kussmaul– Lichtheim model illustrated in Figure 4.4, after incoming speech is processed in the input lexicon, where word recognition takes place, this information then can access the semantic-conceptual field, where word meanings are derived. These semantic-conceptual representations could then access the output lexicon and then Broca’s area, which can program speech output. Since the semantic field codes meanings and concepts, but not phonology, the use of this indirect route might lead to the semantic paraphasic errors associated with deep dysphasia. For example, when a patient with deep dysphasia is asked to repeat the word “sea”, the phonological representation, activated in the input lexicon, may activate the neuronal network that represents the concept of a large body of water. Subsequently, when the neuronal network in the semantic-conceptual field that represents a large body of water accesses the output lexicon, it might activate other lexical representations of large bodies of water such as “ocean”, and therefore the patient with this disorder who is asked to repeat “sea” might say “ocean” rather than “sea”. When normal people are asked to repeat a nonword, they usually can perform this task without difficulty. Throughout life, people hear new words and are often able to learn these words even after one presentation. This observation suggests that both the input and output lexicons can rapidly learn the phoneme sequences that constitute words. Thus, when asked to repeat nonwords, normal people might rapidly learn these nonwords, and in normal people the repetition of nonwords might require the use of the same system as for real words. If patients with a disconnection between the input and output lexicons are asked to repeat real words, they might be able to repeat correctly many of these words, but make occasional semantic paraphasic errors. When they are asked, however, to repeat nonwords, since there is no semantic representation for nonwords, they should not be able to repeat nonwords, and patients with deep dysphasia are severely impaired at repeating nonwords.

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Two forms of transcortical sensory aphasia: asemantic transcortical sensory aphasia and isolation transcortical sensory aphasia According to the modified Wernicke–Kussmaul–Lichtheim model (Figure 4.4), anomic aphasia is induced by inability of the conceptual-semantic representations to access the phonological output lexicon, and transcortical sensory aphasia with intact naming and spontaneous speech is induced by inability of the phonological input lexicon to access the semantic-conceptual field. Transcortical sensory aphasia is induced by either degradation of the semantic-conceptual field or isolation of these representations from both the phonological input and output lexicons. These two forms of transcortical sensory aphasia could be dissociated by nonverbal tests of semantics where, on each trial, the patient attempts to distinguish semantically related objects (from foils). Failure on the test suggests deterioration of the semantic conceptual representations and thus asemantic transcortical sensory aphasia. Good performance on this test suggests the relative preservation, but isolation, of semantic-conceptual representations (Heilman, Tucker, & Valenstein, 1976) that we call isolation transcortical aphasia. Optic and nonoptic aphasia Optic aphasia is another aphasic syndrome for which the Wernicke, Kussmaul, and Lichtheim models cannot account. This disorder was first described by Freund (1889), who reported a patient with right hemianopia that was unable to name objects presented in the visual modality, but could correctly name objects presented in other modalities. In addition, whereas patients with optic aphasia cannot name objects in the visual modality, they can describe and pantomime the use of these objects, suggesting that visual object recognition units can access the semantic-conceptual field, and hence that these patients do not have visual agnosia. Intact naming of objects presented in the tactile and auditory modalities suggests that semantic-conceptual representations have access to the phonological output lexicon. Freund thought this disorder was caused by a disconnection between the visual areas in the occipital lobe and the speech areas in the left hemisphere important for naming. Based on Freund’s postulate, this dissociation could be accounted for on the modified Wernicke–Kussmaul–Lichtheim schema (Figure 4.4) by a functional dissociation between the portion of the brain that contains object recognition units and the phonological output lexicon. This direct, nonsemantic route between object recognition units and the phonological lexicon might also allow people to learn pseudonames for pseudo-objects. Unlike the patients with optic aphasia who can name objects when they are verbally defined, but are impaired when naming seen objects, patients with nonoptic aphasia can name visually presented objects, but cannot name the same objects when a definition of these objects is presented to them (Shuren, Geldmacher, & Heilman, 1993). Since patients with this disorder are able to

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name visually presented objects, their object recognition units are able to access their phonological output lexicon, and this intact lexicon can access Broca’s area. Since these patients’ repetition is intact, the pathway, primary auditory cortex → phonological input lexicon → phonological output lexicon → Broca’s area-motor cortex, is also intact. These patients’ spontaneous speech is characterized by semantic jargon, and they also have poor comprehension. Naming to definition, comprehension, and normal speech all require intact semantic-conceptual representations, and thus these patients’ nonoptic aphasia is probably caused by degradation of their semanticconceptual representations.

Parallel distributed processing (PDP) The information-processing model illustrated in Figure 4.4 can explain almost all known aphasic syndromes. However, this model does not describe how information in these processing modules is stored, although it does explain how these modules interact and communicate. Nadeau (2001) proposed a parallel, distributed processing model based on the Wernicke– Lichtheim information-processing model. In Nadeau’s model, the acoustic module that is akin to Wernicke’s area contains a large number of units that represent the acoustic features of phonemes, and Broca’s area, or what Nadeau calls the articulatory module, contains units that represent discrete articulatory features of speech. Within these language-speech modules, all representations correspond to specific patterns of activity of all the units contained in this module. In addition, each of the units in these modules is connected to the units of other modules, and the entire set of connections between any two modules forms, what has been termed a pattern associator network. During the learning of a language, information is stored by alterations in the strength of the connections between units both within and between modules. For example, the meaning of a spoken word is mediated by the connections between the acoustic module that determines the phonemic structure of the heard word and the module that contains the features of the concept.

Summary This chapter reviews the aphasic syndromes, using both a historic and an information-processing or cognitive diagrammatic modeling approach. The classical information-processing models and diagrams of the Wernicke, Kussmaul, and Lichtheim have been modified to account for more recently described disorders, such as transcortical sensory aphasia with intact spontaneous speech and naming, deep dysphasia, and nonoptic aphasia. In addition to introducing additional modules and connections to the classical Wernicke, Kussmaul, and Lichtheim models, such as an input and output phono-

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logical lexicon, this revised model suggests that there are many parallel processing systems or routes, and parallel processing in normal people might help constrain perturbations (noise) in these systems. Although the revised Wernicke–Kussmaul–Lichtheim model presented here helps us to understand many of the signs and symptoms associated with a variety of aphasic syndromes, it is far from complete, and future research is needed to gain a better understanding of the means by which the brain mediates language and what happens in brain dysfunction.

References Alajouanine, T., Ombredane, A., & Durand, M. (1939). Le Syndrome de la désintégration phonétique dans l’aphasie. Paris: Masson. Bastian, H. C. (1869). Aphasia and other speech defects. London: H. K. Lewis. Broca, P. (1861). Remarques sur le siège de la faculté du language articulé, suivies d’une observation d’aphémie. Bulletin de la Société Anatomique de Paris, 2, 330–357. Feinberg, T. E., Gonzalez-Rothi, L. J., & Heilman, K. M. (1986). “Inner speech” in conduction aphasia. Archives of Neurology, 43, 591–593. Foundas, A. L., Eure, K. F., Luevano, L. F., & Weinberger, D. R. (1998). MRI asymmetries of Broca’s area: The pars triangularis and pars opercularis. Brain and Language, 64, 282–296. Freund, C. S. (1889). Ueber optische Aphasie und Seelenblindheit. Archiv für Psychiatrie und Nervenkhrankheiten, 20, 276–297. Head, H. (1926). Aphasia and kindred disorders of speech (vol. 1, ch. 4, pp. 54–60). Cambridge: Cambridge University Press. Heilman, K. M. (2006). Aphasia and the diagram makers revisited: An update of information processing models. Journal of Clinical Neurology, 2, 149–162. Heilman, K. M., Gonzalez-Rothi, L. J., McFarling, D., & Rottman, A. (1981). Transcortical sensory aphasia with relatively spared spontaneous speech in naming. Archives of Neurology, 38, 236–239. Heilman, K. M., Tucker, D. M., & Valenstein, E. (1976). A case of mixed transcortical aphasia with intact naming. Brain, 99, 415–525. Jacobs, D. H., Shuren, J., Gold, M. Adair, J. C., Bowers, D., Williamson, D. J. G., et al. (1996). Physostigmine pharmacotherapy for anomia. Neurocase, 2, 83–91. Katz, R. B., & Goodglass, H. (1990). Deep dysphasia: Analysis of a rare form of repetition disorder. Brain and Language, 39, 153–185. Kussmaul, A. (1877). Die Störungen der Sprache. Leipzig: Vogel. Lichtheim, L. (1885). On aphasia. Brain, 7, 433–484. Mohr, J. P., Pessin, M. S., Finkelstein, S., Funkenstein, H. H., Duncan, G. W., & Davis, K. R. (1978). Broca aphasia: Pathologic and clinical. Neurology, 28, 311–324. Nadeau, S. E. (2001). Phonology: A review and proposals from a connectionist perspective. Brain and Language, 79, 511–579. Nielsen, J. M. (1951). The cortical components of akinetic mutism. Journal of Nervous and Mental Diseases, 114, 459–461. Rubens, A. B. (1975). Aphasia with infarction in the territory of the anterior cerebral artery. Cortex, 11, 239–250.

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Shuren, J., Geldmacher D., & Heilman, K. M. (1993). Non-optic aphasia. Neurology, 43, 1900–1907. Wernicke, C. (1874). Der aphasische Symptomencomplex. Breslau: Cohn and Weigart.

5

The impact of right-hemisphere lesions on language abilities Theoretic and clinical perspectives Yves Joanette, Ana Inés Ansaldo, Karima Kahlaoui, and André Roch Lecours1

Acquired language impairments following a brain lesion—aphasia—are usually the consequence of a left-hemisphere lesion (Lecours & Lhermitte, 1979). This fact has been known since the nineteenth century. First, came the unpublished, early, but intelligent, observations of a young surgeon, Marc Dax (1836/1865), who treated young soldiers with and without acquired language impairments after saber blows on the left or right side. However, the first published position paper concerning the relationship between language and the left hemisphere is attributed to Paul Broca (1865). Broca clearly stated that the same hemisphere was responsible for the dominant hand and for language, thus linking language abilities and the left hemisphere in righthanders. This statement proved to be largely, but not entirely, true. First, it rapidly became obvious that Broca’s statement only applied to right-handers. The neurobiological bases of language in left-handers and ambidextrals follow other rules that are still unclear, such that a majority of left-handers will become aphasic following a left-hemisphere lesion (Joanette, 1989). Second, there is a small, but measurable, proportion of right-handers in whom language representation appears to depend heavily upon the right hemisphere, as exemplified by the occurrence of crossed aphasia (Bramwell, 1899; Joanette, 1989). Professor Luigi Vignolo contributed significantly to this literature on crossed aphasia. He published the first MRI-ascertained case of crossed aphasia (Faglia & Vignolo, 1990) and contributed to a thorough and critical review of published cases (Faglia, Rottoli, & Vignolo, 1990; Mariën, Engelborghs, Vignolo, & De Deyn, 2001). More than anyone else, Vignolo and his colleagues have made it clear that crossed aphasics’ brain organization does not mirror that usually seen in right-handers, since a righthemisphere lesion frequently affects both language and visuo-spatial abilities (Paghera, Mariën, & Vignolo, 2003). His interest in crossed aphasia has extended until recently, as he has contributed to an impressive and critical review of all cases of crossed aphasia, including some important methodological recommendations for future studies (Mariën, Paghera, De Deyn, &

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Vignolo, 2004). However, even if one limits oneself to right-handers—and to non-exceptional right-handers at that—Paul Broca’s statement is still only partially true. The goal of this chapter is to describe the theoretical aspects and clinical implications of the right hemisphere’s contribution to language abilities, and the impact on communicative abilities of a lesion in that hemisphere. The exclusion of any role for the right hemisphere in language and communication lasted for approximately a century. The recognition of the right hemisphere’s importance to language was due to the clever clinical observations of a limited number of pioneers. Jon Eisenson (1959, 1962) was the first to suspect that right-handers with an acquired lesion in the right hemisphere that did not result in crossed aphasia proper still exhibited “subtle” language impairments, namely at the lexicosemantic level. These findings were immediately supported by Ed Weinstein (1964) and Macdonald Critchley (1962), and a series of clinical observations of the impact of right-hemisphere lesions on some components of language followed. At the same time, there was a growing interest in the linguistic capacities of the isolated right hemisphere, as described in the early cases of split-brain patients (e.g. Code & Joanette, 2003; Sperry & Gazzaniga, 1967). Once again, Luigi Vignolo made a seminal contribution to this question. With his student François Boller, he was the first to use a systematic evaluation procedure developed for aphasia, this time applied to nonaphasic, right-hemisphere-damaged (RHD) individuals (Boller & Vignolo, 1966). Some years later, Vignolo was also among the first to compare left- and right-hemisphere-damaged individuals on phonological and semantic tasks (Faglioni, Spinnler, & Vignolo, 1969). However, as was the case with Jon Eisenson (1959, 1962), Weinstein (1964), and Critchley (1962), Vignolo’s descriptions of the impact of a right-hemisphere lesion on language abilities suffered from the lack of the kind of theoretical framework required to describe fully these impacts: not only were the models of the components of language known at that time limited (e.g. semantic processing of words), but some of the components of language recognized nowadays had not even been thought of (such as discourse processing or pragmatic abilities). Consequently, the impact on language of a righthemisphere lesion was referred to by “impressionistic” concepts, such as “superordinary” aspects of language (Eisenson, 1962), or “latent aphasia” (Boller & Vignolo, 1966). Nevertheless, these contributions were of paramount importance for the field to develop. This chapter offers a summary of the impact of a right-hemisphere lesion on language and communication as recognized now, and discusses the clinical implications of the contributions made in the last 40 years, since the first descriptions by the pioneers, including Luigi Vignolo.

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Language impairments following a right-hemisphere lesion in right-handedness: a description Since the seminal contributions of the pioneers, numerous studies have allowed us to clarify the right hemisphere’s contribution to language processing. There is, however, a distinction to be made between studies reporting on the right hemisphere’s capacity to process language, and studies describing its actual contribution to language abilities (Joanette & Goulet, 1994, 1998). Studies looking at language and the right hemisphere first focused on its linguistic potential, as explored in experimental or quasi-experimental conditions (as in split-brain patients, individuals with anatomical or pharmacological left-hemisphere knockouts). These studies generated myriads of other studies looking at the right hemisphere’s linguistic potential in young adults—usually undergraduates—using the technique of divided visual-field tachistoscopic presentation or, to a lesser degree, dichotic listening presentation (for a review, see Joanette, Goulet, & Hannequin, 1990). The vast majority of these studies used single-word presentations. Taken together, these studies show that the isolated right hemisphere does have the potential to process meaning more than form (such as phonological aspects) of isolated words, and particularly when these words are frequent, concrete, and imageable. However, these studies reveal only that the right hemisphere has some linguistic potential; none of them can demonstrate that this potential is actually necessary for word processing when the left hemisphere is intact (Joanette & Goulet, 1994). Moreover, most of these studies say very little about the right hemisphere’s capacity to process components of language that go beyond the isolated word or sentence, such as discourse or pragmatic components. This is why the most relevant information about the actual contribution of the right hemisphere to language comes from other studies, namely those reporting discrete language impairments following a right-hemisphere lesion, as well as the most recent ones using functional neuroimaging. A number of studies have analyzed the nature of the impact of righthemisphere lesions on language and communicative abilities (Code, 1987; Joanette et al., 1990; Myers, 1999; Tompkins, 1995). The following sections offer a condensed review of the possible impacts of such a lesion. This description benefits from the increasing availability of theoretical frameworks allowing the description of some of these impacts, which were only vaguely described by the pioneers. For instance, the major developments regarding discourse-level processing (e.g. Joanette & Brownell, 1990) now make possible better description and understanding of the impact of such lesions on the ability to process narrative or other types of discourse. In general, it can be said that the occurrence of a right-hemisphere lesion may result in impairments in four different components of language: prosody, semantic processing of words, discourse, and pragmatic abilities. This is, of course, notwithstanding the fact that the same lesion may also significantly affect other cognitive abilities, as is the case when apraxia or spatial neglect is

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present. In the latter case, spatial neglect can determine the presence of what is clinically known as spatial type alexia and/or agraphia (Hécaen & Marcie, 1974). In those individuals, there may be an important interference with reading abilities, while writing can be characterized by the restricted use of the right hemi-page, the lack of horizontality, and the presence of duplicated strokes (e.g. “n” written as “m” and “i” as “u”). Prosody Prosody is the component of language that refers to the cognitive processing needed to understand or express communicative intent by the suprasegmental aspects of speech. These include variations in intonation, pauses, and modulations of vocal intensity. In this chapter, a basic distinction will be made between linguistic and emotional prosody. While the latter allows speakers to express their own emotion about the message, or to process that of the interlocutor, the former is more directly linked to a number of phenomena which operate directly on the linguistic message itself. Linguistic prosody can itself be divided into three phenomena: •

•

•

Lexical stress, which operates at the phoneme/syllable level and, in many languages—including English—makes possible the appropriate expression of a lexeme or the semantic disambiguation of two phonologically similar words (as in ímport versus impórt). This particular aspect of linguistic prosody does not have the same semantic implications in a language, such as French, in which all words have their lexical stress on the same syllable (the final one, in French). Emphatic stress, which operates at the syllable/word level and allows the speaker to emphasize a specific piece of information, usually corresponding to a word (e.g. Paul is eating a lizard versus Paul is eating a lizard ). Modalities, which operate at the sentence level and allow the speaker to express complementary communicative information such as the status of the sentence-based communicative intent (e.g. “The door is open.” versus “The door is open?”).

Many studies have allowed the description of the possible impairments of prosody in RHD individuals, and have compared them with those that can be found in a left-hemisphere lesion. The most characteristic prosodic impairments in RHD individuals involve the processing of emotional prosody and of modality. The fact that emotional prosody can be impaired in RHD individuals is certainly no surprise, given the known contribution of the right hemisphere to the processing of emotions in general (Borod et al., 1996). Recent studies using functional neuroimaging confirm the right hemisphere’s role in the processing of emotions (e.g. Mitchell et al., 2003). However, the fact that RHD individuals may also exhibit impairments in the processing of

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modalities testifies to the existence of a purely linguistic prosodic deficit in these individuals. For example, our group has already encountered an RHD individual in whom the only impairment was to report and express in a declarative modality all types of modalities (e.g. orders, questions) (Théroux, 1987). When such impairments exist, they are referred to as aprosodia or dysprosodia. Ross’s (1981) suggestion that such prosodic impairments mirror in their taxonomy and lesion localization the different clinical types of aphasia has not proven to be either empirically confirmed or clinically useful. Prosodic impairments in individuals with left-hemisphere lesions appear to be qualitatively different from those reported in RHD individuals, as they frequently interfere with the ability to process lexical stress. In this case, as is true of many components of cognition, the role of each hemisphere appears to be complementary, supporting the idea of interhemispheric cooperation (Sergent, 1994). In fact, apart from the emotional content itself, it looks as if a right-hemisphere lesion interferes with the processing of those aspects of prosody that arise from suprasyllable or word processing, as is the case with modality. This would be consistent with the right hemisphere’s suspected superiority in the processing of large time-scale acoustic events. Indeed, studies looking at the processing of melodic curves as a component of musical abilities also point to the privileged role of the right hemisphere (e.g. Peretz & Babaï, 1992). In summary, impairments of prosody may be the result of either a right- or a left-hemisphere lesion. However, the prosodic impairments in RHD individuals appear to be more specific to the processing of emotional prosody, as well as large time-scale-based prosodic components such as modalities. Semantic processing of words A fair number of studies have looked at the impact of a right-hemisphere lesion on word processing. Most looked at written-word comprehension, while a limited number described impairments on the expressive side. Briefly, such impairments affect the semantic processing of words more than their formal (such as phonological or morphological) dimensions, and they appear to affect particularly words that are infrequent, abstract or nonimageable (Joanette et al., 1990). Since this description may express impairments in the most resource-demanding types of word processing (see below), the quest for possible impairments that are specific to a right-hemisphere lesion has been intense. Two examples of word-processing impairments that may be characteristic of a right-hemisphere lesion are described below. Difficulty in the processing of the alternative metaphorical meanings of polysemic words (Brownell et al., 1990; Gagnon et al., 2003) Convergent observations tend to indicate that a right-hemisphere lesion may result in an impairment of the processing of the alternative metaphorical

98 Joanette et al. meanings of polysemic words. For example, RHD individuals may have more difficulty in perceiving the alternative metaphorical meaning “love” of the polysemic word warm (the literal associate being temperature), as compared to the alternative nonmetaphorical meaning “student” of the polysemic word pupil (the literal associate being eye) (examples taken from Brownell et al., 1990). Although care was taken to eliminate the possibility that the problem might simply be a general difficulty in the processing of any alternative meanings (Brownell et al., 1990), there is still some doubt whether this impairment is specific to RHD individuals (Gagnon et al., 2003). It remains the case, however, that the processing of the alternative metaphorical meanings of polysemic words is frequently presented as an example of a specific word-processing impairment following a right-hemisphere lesion. Tendency to activate low-predictability semantic relationships in word production tasks (Le Blanc & Joanette, 1996) It is well known that a right-hemisphere lesion interferes with normal performance on a verbal fluency (or word-naming) task. Numerous studies have suggested that RHD individuals perform worse than matched controls on word-naming tasks in which the production criterion is semantic (such as “animals”) but not when it is orthographic (as in words starting with the letter l; Cardebat et al., 1990; Goulet et al., 1997; Joanette & Goulet, 1986; Koivisto & Laine, 1999). Such an impairment appears, moreover, to be more frequent when the production criterion is particularly productive; that is, it allows for a large number of items (animals versus birds). However, none of these characterizations appear to be specific to a right-hemisphere lesion. In looking for such an impairment, one study that used an unconstrained oral naming paradigm suggested that the production of low-predictability items (items that were rated as having a low degree of prototypicality with regard to the natural semantic cluster in which they were produced) might be the only specific impairment characterizing the oral naming of RHD individuals (Le Blanc & Joanette, 1996). This characteristic of RHD individuals may express a lesser lateral inhibition in the semantic activation pattern of RHD individuals, a tendency which could be coherent with RHD individuals’ general tendency to produce tangential discourse (e.g. Gardner et al., 1983). According to some theoretical frameworks, there are a number of other possible semantic impairments that might be shown specifically to characterize individuals with a right-hemisphere lesion. Although at this point they are still unproven, the following examples represent theory-based expected specific impairments in RHD individuals. Only future studies will indicate whether such expected specific impairments are indeed found in RHD individuals.

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Depth/spread of activation and coarseness of coding hypotheses (Beeman, 1998; Chiarello, 1998) According to these two related hypotheses, the neural networks sustained by the right hemisphere do not semantically process words in the same way as those in the left hemisphere. The right hemisphere processes the semantics of words in a more shallow and less focal manner, using a coarse (versus finegrained) coding strategy. For example, the activation of a given semantic node would result in less focused activation propagation in the right hemisphere, thus favoring the activation of categorical—cohyponymic—relationships as a result of the left-hemisphere activation, and remotely associated functional— experiential—links in the right hemisphere (Chiarello, 1998). A different way of referring to a somewhat similar distinction is Beeman’s (1998) suggestion that the right hemisphere processes the semantics of words through a coarse semantic coding process, while the left hemisphere uses fine-grained coding. If these two hypotheses (or one of them) are right, then a right-hemisphere lesion would be distinguished by a greater impact on the individual’s ability to perform on functional, as opposed to categorical, semantic links. However, it should be mentioned here that any such prediction is very daring, since it is very difficult to predict a putatively specific impairment on the basis of a greater potential noted in the normal brain dynamics (Joanette & Goulet, 1994). Time-course hypothesis (Burgess & Simpson, 1988; Koivisto, 1997) A second hypothesis represents to some extent the right hemisphere’s superior processing of large time-scale acoustic events, as described above. According to the results obtained by these authors, the propagation of the activation in the semantic network sustained by the left hemisphere appears to activate both closely and remotely linked nodes. However, this activation is probably relatively brief as compared to that sustained by the right hemisphere, in which the activation of distantly related information starts later, but lasts longer. Thus, the right hemisphere is characterized by the fact that the semantic activation it sustains allows for longer-lasting activation of more remote nodes in a smaller number. Again, if anything can be predicted about the impact of a right-hemisphere lesion, it could be expected that such a lesion would interfere most with longer-lasting activation, particularly of remotely linked semantic nodes. Inter-/intraconceptual hypothesis (Drews, 1987; Nocentini et al., 2001) Another way of referring to a similar view of the right hemisphere’s semantic characteristics has been proposed in reference to the nature of semantic relationships (Drews, 1987). According to Drews, the right hemisphere is particularly efficient in the activation of interconceptual links (that is, functional and

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experiential), while the left hemisphere is more efficient at activating intraconceptual links (that is, categorical). Measuring the inter- versus intraconceptual sensitivities between left-hemisphere-damaged and RHD individuals, Nocentini et al. (2001) obtained results that only partially support this prediction. More studies are needed to verify this hypothesis, as well as the three others described here. The possibility that some impairments of the semantic processing of words might be specific to RHD individuals does not mean that an acquired righthemisphere lesion would not also have some nonspecific impacts. Indeed, many of the “subtle” impairments noted in RHD individuals’ language and communication abilities could also express the impact of limited access to or availability of cognitive resources (Joanette & Goulet, 1998; Monetta & Champagne, 2004; Monetta & Joanette, 2001, 2003). Although still unproven, the hypothesis that limited access to cognitive resources might account, at least in part, for the impaired semantic processing of words by RHD individuals is indirectly supported by the fact that some impairment patterns presumed to be specific to RHD individuals have been reproduced in normal individuals whose cognitive resources were temporarily limited by a dual-task condition (Monetta et al., 2003). In summary, the integrity of the right hemisphere of right-handers appears crucial to the full semantic processing of words. A number of word semantic impairments following a right-hemisphere lesion have been described. It is not certain, however, which of those are specific to a right-hemisphere lesion—a limitation that does not diminish the fact that RHD individuals have to live with some of these impairments. There is also a possibility that these impairments, as well as those of the discourse and pragmatic components, also reflect the fact that a right-hemisphere lesion is responsible for limited resource availability, a condition resembling that observed in left-hemispheredamaged, aphasic individuals (e.g. McNeil, Odell, & Tseng, 1991). Discourse abilities Discourse impairments, whether receptive or expressive, represent one of the possible manifestations of communicative impairments in individuals suffering from a right-hemisphere lesion (Joanette et al., 1990). RHD individuals’ conversation has been described as inappropriate in its context and its form (such as turn-taking), with tangential topic shifts, and an overall feeling of lack of appreciation of the gist of the communicative exchange, as well as a lack of reaction to unexpected content (such as humor). However, more systematic descriptions of RHD discourse impairments have been made with regard to narrative discourse abilities, essentially because of the availability of more comprehensive theoretical frameworks (Brownell & Joanette, 1993; Frederiksen et al., 1990). The narrative abilities of RHD individuals have been examined in many ways. Although available, the formal aspects of RHD narratives (such as

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noun/verb ratio) have not been the focus of much attention, since a righthemisphere lesion definitely affects the content (semantic) more than the form of communication. Thus, the most relevant descriptions of RHD discourse refer to its organization and its semantic content. These studies have pointed to a number of possible characteristics, briefly summarized here (e.g. Joanette et al., 1986; Stemmer & Joanette, 1998). •

• •

a tendency to produce incoherent discourse expressed through erroneous or absent anaphoric references, a tendency to digress or to shift tangentially on a topic, and an absence of topic/theme progression and/or relation impoverished informative content in terms of the quantity of information conveyed with reference to a given quantity of words/sentences difficulty in processing some types of inferences, particularly bridging inferences (such as inferences allowing the reinterpretation of a narrative with reference to the global framework, such as the reinterpretation of a narrative of an accident in the more global framework of a dream, as indicated by late-arriving information).

It is important to mention that the narrative discourse impairments described in RHD individuals do not appear to be pathognomonic; that is, specific to a right-hemisphere lesion. In fact, some of the characteristics described here as “impairments” can also be seen in “normal” individuals (Joanette et al., 1986) or in individuals with other kinds of traumatic brain injury. Consequently, the occurrence of narrative discourse impairments can certainly not be taken as exclusive to individuals with a right-hemisphere lesion. In summary, discourse abilities, whether conversational or narrative, can be impaired following a right-hemisphere lesion. The exact nature of these impairments is still the object of many studies. Though these impairments are not exclusive to individuals with a right-hemisphere lesion, they certainly represent a dimension of their communicative deficit that deserves attention and care. Pragmatic abilities The pragmatic component of language represents another important aspect of communication that allows for a better appreciation of language impairments in RHD individuals. The theoretical frameworks of pragmatics (e.g. Searle, 1969) were, however, first introduced 10 years after the first description of language impairments in RHD individuals (Eisenson, 1959). It has since been recognized quite clearly that RHD individuals may suffer from inadequate and incomplete communicational abilities in natural contexts (e.g. Gardner et al., 1983). Since then, the development of pragmatic theories has made a major contribution to our understanding of pragmatic impairments in RHD individuals.

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Although pragmatics has long been conceived as merely the relationship between the verbal message and the context in which this verbal message is expressed or captured, current proposals insist on the fact that pragmatics corresponds to the ability to process—express or understand—communicative intent by reference to a given context (Gibbs, 1999). Such pragmatic abilities are required to understand the true meaning of sarcastic or humorous speech, or the exact sense of indirect speech acts, and to adjust the content and form of a message according to the perceived shared knowledge. In fact, in everyday life, it is quite rare for people to express a given communicative intention precisely and specifically; in fact, this contributes to the pleasure of verbal communication. In this respect, many impairments of pragmatic abilities have been reported over the last two decades. Impairment of the appreciation of humor or sarcasm (e.g. Gardner et al., 1975; Wapner, Hamby, & Gardner, 1981) Many studies have suggested that RHD individuals exhibit difficulty in appreciating and understanding discourse segments in which the real intention is greater than or different from that expressed on the surface, with reference to a given communication context (e.g. This is a very smart comment!). Unfortunately, though, many of these studies suffer from methodological limitations that make it impossible to know whether such “impairments” exist by themselves, or whether they appear only when the individual is put in the context of a forced-choice task (Joanette & Goulet, 1994). Be that as it may, clinical observations do tend to suggest the existence of such deficits, which affect RHD individuals’ ability to fully understand the communicative intention beyond the surface discourse. Impairment of indirect speech act processing (Foldi, 1987; Stemmer, Giroux, & Joanette, 1994; Vanhalle et al., 2000) Indirect speech acts (Searle, 1969) are another type of discourse in which the communicative intent is not explicitly expressed in the verbal message (e.g. It is quite warm here! in order to convey Open the window!). Numerous studies have shown that RHD individuals exhibit indirect speech act deficits. However, according to Stemmer et al. (1994), such deficits are present only for nonconventional indirect speech acts. Thus, RHD individuals have no problem in processing conventional speech acts such as Do you have the time? Their difficulties arise when they are faced with previously unknown indirect speech acts that require an analysis in context in order to be understood. Other studies have insisted that such deficits are generally present when an RHD individual is subjected to a condition that demands a metacognitive analysis in a context that is not familiar (Vanhalle et al., 2000).

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Deficits in taking shared knowledge into consideration (Chantraine, Joanette, & Ska, 1998) Other studies have shown that RHD individuals have difficulty taking into account the common knowledge shared with the interlocutor. Indeed, using a common reference construction task, Chantraine et al. (1998) showed that RHD individuals do not adequately take into account what they should know about their interlocutors’ common knowledge in order to adjust their communicative intent accordingly. Pragmatic disabilities appear to characterize the communication abilities of some RHD individuals. The reasons underlying such deficits are still unknown, however. While some authors have suggested that they may result from the presence of inferencing deficits—an explanation which has been only partially supported (Hamel, Giroux, & Joanette, 2003)—or from a limitation in cognitive resource availability (Monetta et al., 2003), the discussion is still open (McDonald, 2000). One possibility is that the pragmatic deficits in RHD individuals might be due to some deficit of theory of mind abilities (Winner et al., 1998). However, it is uncertain whether the theory of mind and the pragmatic abilities really refer to independent cognitive constructs. Recently, Champagne, Desautels, and Joanette (2004) reported that RHD individuals with pragmatic and theory of mind deficits are characterized by the coexistence of lower executive functions, and particularly those having to do with inhibition, rather than mental flexibility. In summary, pragmatic deficits can result from a lesion of the right hemisphere. Such deficits appear to coexist with limitations in theory of mind abilities. However, the exact source of these deficits—whether this is a specific cognitive ability or a general resource limitation—is still unclear. The fact remains that individuals with a right-hemisphere lesion may suffer from deficits that interfere significantly with everyday communication abilities.

Incidence and distinctive profiles of communication impairments in RHD individuals Very few studies have looked directly at the incidence and the possible different clinical profiles of communicative impairments in RHD individuals. Although no population-based study has yet been done on this subject, clinical experience makes it very clear that not all RHD individuals suffer from the communicative deficits described here. According to Joanette, Goulet, and Daoust (1991), one can suspect that about 50% of all RHD individuals exhibit one or more of these communicative deficits. This proportion is similar to the proportion of left-hemisphere-damaged individuals who suffer from a persistent language disorder (aphasia). When present, such deficits appear to be the consequence of a cortical lesion (Joanette et al., 1983), usually in the perisylvian area, as is the case for aphasia. Another important observation concerns the nature of the communicative

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impairments when present. Just as with aphasia, not all RHD individuals with communicative impairments show the same pattern of deficits (Joanette et al., 1991): in some cases, only one of the components described will be affected (prosody, or semantic processing of words, discourse, or pragmatics). In other cases, more than one component will be impaired, and contrasting clinical patterns of communicative impairments can then be observed. A recent study by Coté et al. (2007) confirms the presence of subtypes of clinical profiles of communication impairments among RHD individuals. In this study, only a small percentage of RHD individuals had normal or nearnormal communicative abilities as evaluated by the MEC battery (Joanette et al., 2004), a clinical protocol which allows the description of possible impairments in prosody, lexical-semantics, discourse, and pragmatic abilities. Given the fact that the RHD individuals included in this study were all undergoing rehabilitation in a specialized center, this result probably expresses the higher incidence of communication impairments in this overselected RHD population. However, the results do point to at least three subtypes of clinical profiles whose relationship with lesion sites and other characteristics still has to be explored. In summary, communicative impairments can be observed in about half of all RHD individuals. When present, these impairments can take different clinical forms, from the isolated impairment of one communicative component to the contrasting clinical profiles associated with the impairment of more than one such component. Consequently, clinicians should be very careful and should not expect all RHD individuals to experience such deficits.

The challenge of the clinical label The previous sections have summarized, in general terms, the different communicative impairments which can occur following a right-hemisphere lesion in right-handers. It has been suggested that approximately half of all RHD individuals may exhibit such impairments, a figure which is grossly comparable to the proportion of left-hemisphere-damaged individuals with persistent aphasia. However, whereas acquired language disorders following a lefthemisphere lesion are clearly referred to as aphasia, the clinical labels used for the communicative impairments following a right-hemisphere lesion are much more diverse. Labels such as cognitive-linguistic disorders, verbal communication impairments, or even nonaphasic acquired language disorders have been used in the past. Although meant to distinguish these deficits from “genuine” aphasia, these labels have become a growing source of confusion. Indeed, some aphasiologists are tempted to force into the clinical label the explanation for the impairments observed. This corresponds to a perversion of the clinical label, which is meant to be a simple descriptor, not an explanation of the clinical phenomenon. But why are we faced with such a labeling challenge?

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The study of aphasia has benefited from numerous early-nineteenth-century contributions. This is clearly an advantage, since aphasia has always been a window into the functional organization of the brain for cognition. However, the study of aphasia has also suffered from its early description, since the “definition” of its clinical descriptors appears to have frozen in time in the late nineteenth century. Indeed, the definition of aphasia—an acquired language disorder following a brain lesion—appears to rely upon the definition of language at that time, essentially referring to articulation, phonology, lexical semantics, and morphosyntax. However, as explained in this chapter, the concept of language has evolved a great deal since the nineteenth century. Abilities such as discourse or pragmatics were only added to our understanding of language in the late twentieth century. Although, at first, there was some hesitation about considering discourse and pragmatics as part of language itself, their position is now very clear. Pragmatics, for example, has evolved from a definition as the mere context in which language occurs to recognition as a component of language (Gibbs, 1999). The position of pragmatics is so clear that Noam Chomsky himself now considers it to be a central component of any linguistic theory that aims to be comprehensive (Stemmer, 1999). Consequently, if discourse and pragmatic abilities are now considered as an inherent part of language abilities, and if aphasia is defined as an acquired language disorder following a brain lesion—without any reference to its etiology or localization—it follows that the communicative impairments that can be found in half of all RHD individuals represent newly described forms of aphasia (Joanette & Ansaldo, 1999, 2000). Not recognizing this obvious fact, and maintaining the opinion that such impairments are “nonaphasic”, would be like neuropsychology arbitrarily segregating amnesic and nonamnesic memory impairments, or apraxic and nonapraxic gesture impairments. There is no reason for these communicative impairments not to be simply included as new instances of the general family of aphasia. If so, then new forms of aphasias will have to be introduced (such as pragmatic aphasia to describe RHD individuals whose impairments affect only their pragmatic abilities). Of course, including these deficits within aphasia does not contribute in any way to better understanding of their causes. However, from a clinical standpoint, it ensures that those RHD individuals will benefit from the same attention and care that left-hemisphere aphasic individuals receive.

Summary and conclusion In summary, a lesion of the right hemisphere of right-handers can result in verbal communication impairments. The recent development of theoretical frameworks with regard to discourse and pragmatic abilities, among others, now allows us to recognize and describe these impairments. The goal of this chapter was to offer an overview of the verbal communication deficits that can be found in RHD individuals. These deficits can interfere, at different

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levels, with prosody, the semantic processing of words, and discourse and pragmatic abilities. Such impairments appear to be present in about half of RHD patients and, when present, can result in different clinical profiles. These deficits raise the question of their labeling and their relationship with aphasia. Given the evolution of the concept of language and the universal definition of aphasia, it is proposed that these deficits correspond to another manifestation of aphasia, thus challenging the idea that they are of a “nonaphasic” nature. The association between the left hemisphere of right-handers and language abilities has now become more nuanced. The right hemisphere of righthanders has also been shown to possess some ability to process certain components of language, mostly related to content. In line with this described potential, a right-hemisphere lesion has been shown to result, in some individuals, in isolated or co-occurring impairments of prosody, the semantic processing of words, discourse abilities, and pragmatic abilities. Though the exact sources of these impairments are still largely unknown, it is thought that they correspond either to deficits specific to RHD individuals, to impairments that can be seen in both left- and right-hemisphere-lesioned individuals, and/or to the nonspecific impact of the limited availability of cognitive resources. When present, these impairments interfere with everyday life to the point that they represent a major communicative handicap. It is proposed that, because such deficits affect components of communication now included within the concept of language, these individuals should be referred to as aphasic patients and should benefit from the same attention and care as conventionally defined aphasic patients. Such a view of the right hemisphere’s contribution to language does not simplify things, but language is a very complex human activity that ranges from the communicative intention to the articulation/gesture, and from the acoustic/visual message analysis to the extraction of the communicative intention. Obviously, language abilities represent a key example of the need for the two hemispheres (Sergent, 1994) of the brain to cooperate fully.

Acknowledgments This work was supported by grants from the CIHR (Canadian Institutes of Health Research) (no. MOP-15006) and from the Heart and Stroke Foundation of Canada (no. YJ-13-FMCQ) to Yves Joanette.

Note 1 Professor André Roch Lecours passed away on 12 June 2005. He was a good friend of Professor Vignolo and admired his work.

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References Beeman, M. (1998). Coarse semantic coding and discourse comprehension. In M. Beeman and C. Chiarello (Eds.), Right hemisphere language comprehension: Perspectives from cognitive neuroscience (pp. 255–284). Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Boller, F., & Vignolo, L. A. (1966). Latent sensory aphasia in hemisphere-damaged patients: An experimental study with the Token Test. Brain, 89, 815–830. Borod, J. C., Rorie, K. D., Haywood, C. S., Andelmand, F., Obler, L. K., Welkowitz, J., et al. (1996). Hemispheric specialization for discourse reports of emotional experiences: Relationships to demographic, neurological, and perceptual variables. Neuropsychologia, 34, 351–359. Bramwell, B. (1899). On “crossed” aphasia and the factors which go to determine whether the “leading” or “driving” speech centers shall be located in the right or in the left hemisphere of the brain, with notes of a case of “crossed” aphasia (aphasia with right-sided hemiplegia) in a left-handed man. Lancet, 3, 1473–1479. Broca, P. (1865). Sur la faculté du language articulé. Bulletin de la Société d’Anthropologie, 6, 337–393. Brownell, H. H., & Joanette, Y. (1993). Narrative discourse in neurologically impaired and normal aging adults. San Diego, CA: Singular Publishing Group. Brownell, H. H., Simpson, T. L., Bihrle, A. M., Potter, H. H., & Gardner, H. (1990). Appreciation of metaphoric alternative word meanings by left and right braindamaged patients. Neuropsychologia, 28, 375–383. Burgess, C., & Simpson, G. (1988). Cerebral hemispheric mechanisms in the retrieval of ambiguous word meanings. Brain and Language, 33, 86–103. Cardebat, D., Doyon, B., Puel, M., Goulet, P., & Joanette, Y. (1990). Évocation lexicale formelle et sémantique chez des sujets normaux. Performances et dynamiques de production en fonction du sexe, de l’âge et du niveau d’étude. Acta Neurologica Belgica, 90, 207–217. Champagne, M., Desautels, M. C., & Joanette, Y. (2004). Accounting for the pragmatic deficit in RHD individuals: A multiple case study. Brain and Language, 87, 210–211. Chantraine, Y., Joanette, Y., & Ska, B. (1998). Conversational abilities in patients with right hemisphere damage. In M. Paradis (Ed.), Pragmatics in neurogenic communication disorders (pp. 21–32). Tarrytown, NY: Pergamon Press (Elsevier Science, Inc.). Chiarello, C. (1998). On codes of meaning and the meaning of codes: Semantic access and retrieval within and between hemispheres. In M. Beeman & C. Chiarello (Eds.), Right hemisphere language comprehension: Perspectives from cognitive neuroscience (pp. 141–160). Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Code, C. (1987). Language, aphasia and the right hemisphere. Chichester: Wiley. Code, C., & Joanette, Y. (2003). The control of speech in the adult brain: The disconnected right hemispheres of PS, VP, and JW. In C. Code, C.-W. Wallesch, Y. Joanette & A. R. Lecours (Eds.), Classic cases in neuropsychology (vol. II, ch. 9, pp. 109–129). Hove: Psychology Press. Coté, H., Payer, M., Giroux, F. & Joanette, Y. (2007). Towards a description of clinical communication impairment profiles following right-hemisphere damage. Aphasiology (special issue), 21 (6/7/8), 739–749. Critchley, M. (1962). Speech and speech-loss in relation to duality of the brain.

108

Joanette et al.

In V. B. Mountcastle (Ed.), Interhemispheric relations and cerebral dominance (pp. 208–213). Baltimore, MD: Johns Hopkins Press. Dax, M. (1836/1865). Lésions de la moitié gauche de l’encéphale coïncidant avec l’oubli des signes de la pensée (Lu au Congrès méridional tenu à Montpellier en 1836). Gazette Hebdomadaire de Médecine et de Chirurgie, 2e série, 2, 259–262. Drew, E. (1987). Qualitatively different organizational structures of lexical knowledge in the left and right hemisphere. Neuropsychologia, 25, 419–427. Eisenson, J. (1959). Language dysfunctions associated with right brain damage. American Speech and Hearing Association, 1, 107. Eisenson, J. (1962). Language and intellectual modifications associated with right cerebral damage. Language and Speech, 5, 49–53. Faglia, L., Rottoli, M. R., & Vignolo, L. A. (1990). Aphasia due to lesions confined to the right hemisphere in right handed patients: A review of the literature including the Italian cases. Italian Journal of Neurological Sciences, 11, 131–144. Faglia, L., & Vignolo, L. A. (1990). A case of “crossed aphasia” in which the integrity of the left hemisphere is assessed by MRI. Italian Journal of Neurological Sciences, 11, 51–55. Faglioni, P., Spinnler, H., & Vignolo, L. A. (1969). Contrasting behavior of right and left hemisphere-damaged patients on a discriminative and a semantic task of auditory recognition. Cortex, 5, 366–389. Foldi, N. S. (1987). Appreciation of pragmatic interpretations of indirect commands: Comparison of right and left hemisphere brain-damaged patients. Brain and Language, 31, 88–108. Frederiksen, C. H., Bracewell, R. J., Breuleux, A., & Renaud, A. (1990). The cognitive representation and processing of discourse: Function and dysfunction. In Y. Joanette & H. H. Brownell (Eds.), Discourse ability and brain damage: Theoretical and empirical perspectives (pp. 69–110). New York: Springer-Verlag. Gagnon, L., Goulet, P., Giroux, F., & Joanette, Y. (2003). Processing of metaphoric and non-metaphoric alternative meanings of words after right- and left-hemispheric lesion. Brain and Language, 87, 217–226. Gardner, H., Brownell, H. H., Wapner, W., & Michelow, D. (1983). Missing the point: The role of the right hemisphere in the processing of complex linguistic materials. In E. Perecman (Ed.), Cognitive processing in the right hemisphere (pp. 169–191). New York: Academic Press. Gardner, H., Ling, P. K., Flamm, L., & Silverman, J. (1975). Comprehension and appreciation of humor in brain-damaged patients. Brain, 98, 399–412. Gibbs, R. W., Jr. (1999). Interpreting what speakers say and implicate. Brain and Language, 68, 466–485. Goulet, P., Joanette, Y., Sabourin L., & Giroux, F. (1997). Word fluency after a right-hemisphere lesion. Neuropsychologia, 35, 1565–1570. Hamel, C., Giroux, F., & Joanette, Y. (2003). Inferential abilities in right-hemispheredamaged individuals: Looking for subgroups. Brain and Language, 87, 206–207. Hécaen, H., & Marcie, P. (1974). Disorders of written language following right hemisphere lesions: Spatial dysgraphia in hemisphere function in the human brain. In S. J. Dimond & J. G. Beaumont (Eds.), Hemispheric functions in the human brain (pp. 345–365). New York: Wiley. Joanette, Y. (1989). Aphasia in left-handers and crossed aphasia. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology (vol. 2, pp. 173–183). Amsterdam: Elsevier.

5. Right-hemisphere lesions and language

109

Joanette, Y., & Ansaldo, A. I. (1999). Clinical note: Acquired pragmatic impairments and aphasia. Brain and Language, 68, 529–534. Joanette, Y., & Ansaldo, A. I. (2000). The ineluctable and interdependent evolution of the concepts of language and aphasia. Brain and Language, 71, 106–109. Joanette, Y., & Brownell, H. H. (Eds.) (1990). Discourse ability and brain damage: Theoretical and empirical perspectives. New York: Springer-Verlag. Joanette, Y., & Goulet, P. (1986). Criterion-specific reduction of verbal fluency in right brain-damaged right-handers. Neuropsychologia, 24, 875–879. Joanette, Y., & Goulet, P. (1994). Right hemisphere and verbal communication: Conceptual, methodological, and clinical issues. Clinical Aphasiology, 22, 1–23. Joanette, Y., & Goulet, P. (1998). Right hemisphere and the semantic processing of words: Is the contribution specific or not? In E. G. Visch-Brink & R. Bastiaanse (Eds.), Linguistic levels in aphasiology (pp. 19–34). San Diego, CA: Singular Publishing Group. Joanette, Y., Goulet, P., & Daoust, H. (1991). Incidence et profils des troubles de la communication verbale chez les cérébrolésés droits. Revue de Neuropsychologie, 1, 3–27. Joanette, Y., Goulet, P., & Hannequin, D. (with the collaboration of Boeglin, J.) (1990). Right hemisphere and verbal communication. New York: Springer-Verlag. Joanette, Y., Goulet, P., Ska, B., & Nespoulous, J.-L. (1986). Informative content of narrative discourse in right-brain-damaged right-handers. Brain and Language, 29, 81–105. Joanette, Y., Lecours, A. R., Lepage, Y., & Lamoureux, M. (1983). Language in righthanders with right-hemisphere lesions. A preliminary study including anatomical, genetic, and social factors. Brain and Language, 20, 217–248. Joanette, Y., Ska, B., & Côté, H. (with the collaboration of Daigle, M. A., Delmas, A. M., Delyfer, A., Eck, K., Forté, D., Généreux, S., et al.) (2004). Protocole MEC (Protocole Montréal d’Évaluation de la Communication). Isbergues, France: Ortho édition. Koivisto, M. (1997). Time course of semantic activation in the cerebral hemispheres. Neuropsychologia, 35, 497–504. Koivisto, M., & Laine, M. (1999). Strategies of semantic categorization in the cerebral hemispheres. Brain and Language, 66, 341–357. Le Blanc, B., & Joanette, Y. (1996). Unconstrained oral naming in left- and righthemisphere-damaged patients: An analysis of naturalistic semantic strategies. Brain and Language, 55, 42–45. Lecours, A. R., & Lhermitte, F. (1979). L’Aphasie. Paris: Flammarion. Mariën, P., Engelborghs, S., Vignolo, L. A., & De Deyn, P. P. (2001). The many faces of crossed aphasia in dextrals: Report of nine cases and review of the literature. European Journal of Neurology, 8, 643–658. Mariën, P., Paghera, B., De Deyn, P. P., & Vignolo, L. (2004). Adult crossed aphasia in dextrals revisited. Cortex, 40, 41–74. McDonald, S. (2000). Exploring the cognitive basis of right-hemisphere pragmatic language disorders. Brain and Language, 75, 82–107. McNeil, M., Odell, K., & Tseng, C. (1991). Toward the integration of resource allocation into a general theory of aphasia. In T. E. Prescott (Ed.), Clinical aphasiology, vol. 20. Austin, TX: Pro-Ed. Mitchell, R. L., Elliott, R., Barry, M., Cruttenden, A., & Woodruff, P. W. (2003). The neural response to emotional prosody, as revealed by functional magnetic resonance imaging. Neuropsychologia, 41, 1410–1421.

110

Joanette et al.

Monetta, L., & Champagne, M. (2004). Processus cognitifs sous-jacents déterminant les troubles de la communication verbale chez les cérébrolésés droits. Rééducation orthophonique, 219, 27–41. Monetta, L., Champagne, M., Desautels, M.-C., & Joanette, Y. (2003). Impact of resources restriction on processing of non-literal utterances. Brain and Language, 87, 208–209. Monetta, L., & Joanette, Y. (2001). Word processing impairments among right hemisphere-damaged patients: Deficits in cognitive resources? Poster presented at the 25th World IALP Congress, Montreal, 5–9 August. Monetta, L., & Joanette, Y. (2003). Specificity of the right hemisphere’s contribution to verbal communication: The cognitive resources hypothesis. Journal of Medical Speech-Language Pathology, 11, 203–211. Myers, P. S. (1999). Right hemisphere damage: Disorders of communication and cognition. San Diego, CA: Singular Publishing Group. Nocentini, U., Goulet, P., Roberts, P. M., & Joanette, Y. (2001). The effects of leftversus right-hemisphere lesions on the sensitivity to intra- and interconceptual semantic relationships. Neuropsychologia, 39, 443–451. Paghera, B., Mariën, P., & Vignolo, L. A. (2003). Crossed aphasia with left spatial neglect and visual imperception: A case report. Neurological Sciences, 23, 317–322. Peretz, I., & Babaï, M. (1992). The role of contour and intervals in the recognition of melody parts: Evidence from cerebral asymmetries in musicians. Neuropsychologia, 30, 277–292. Ross, E. (1981). The aprosodias: Functional-anatomical organization of the affective components of language in the right hemisphere. Archives of Neurology, 38, 561–569. Searle, J. R. (1969). Speech acts. Cambridge: Cambridge University Press. Sergent, J. (1994). Spécialisation fonctionnelle et coopération des hémisphères cérébraux. In X. Seron & M. Jeannerod (Eds.), Neuropsychologie humaine (pp. 105–125). Liège: Mardaga. Sperry, R. W., & Gazzaniga, M. S. (1967). Language following surgical disconnection of the hemispheres. In C. H. Millikan & F. L. Darley (Eds.), Brain mechanisms underlying speech and language (pp. 108–121). New York: Grune and Stratton. Stemmer, B. (1999). An on-line interview with Noam Chomsky: On the nature of pragmatics and related issues. Brain and Language, 68, 393–401. Stemmer, B., Giroux, F., & Joanette, Y. (1994). Production and evaluation of requests by right hemisphere brain-damaged individuals. Brain and Language, 47, 1–31. Stemmer, B., & Joanette, Y. (1998). The interpretation of narrative discourse of braindamaged individuals within the framework of a multi-level discourse model. In M. Beeman & C. Chiarello (Eds.), Right hemisphere language comprehension: Perspectives from cognitive neuroscience (pp. 329–348). Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Théroux, A.-M. (1987). Trouble de la prosodie suite à une lésion hémisphérique droite: une étude de cas. Thesis. Montreal: Université de Montréal. Tompkins, C. A. (1995). Right hemisphere communication disorders: Theory and management. San Diego, CA: Singular Publishing Group. Vanhalle, C., Lemieux, S., Joubert, S., Goulet, P., Ska, B., & Joanette, Y. (2000). Processing of speech acts by right hemisphere brain-damaged patients: An ecological approach. Aphasiology, 14, 1127–1141. Wapner, W., Hamby, S., & Gardner, H. (1981). The role of the right hemisphere in the apprehension of complex linguistic materials. Brain and Language, 14, 15–33.

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Weinstein, E. A. (1964). Affections of speech with lesions of the non-dominant hemisphere. Research Publications of the Association for Research in Nervous and Mental Disease, 42, 220–228. Winner, E., Brownell, H., Happé, F., Blum, A., & Pincus, D. (1998). Distinguishing lies from jokes: Theory of mind deficits and discourse interpretation in right hemisphere brain-damaged patients. Brain and Language, 62, 89–106.

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Acquired dyslexia and dysgraphia Ria De Bleser and Claudio Luzzatti

Classical and cognitive neuropsychological approaches to graphemic processing Acquired dyslexia and dysgraphia refer to disturbances in reading and writing in a previously competent reader/writer subsequent to brain damage (as in stroke or closed head injury). Contemporary studies of acquired dyslexia and dysgraphia emphasize patterns of preserved and impaired abilities in order to understand the mental processing architecture in normals. This objective has been explicitly stated in the program of modern cognitive neuropsychology, which was established especially by the new approach taken to acquired disorders of written language. In the previous, syndrome-oriented, neuropsychological paradigm, the focus of attention was predominantly on acquired disorders of the spoken language system (aphasia), their classification, and their lesion correlation. Because reading and writing skills develop after the acquisition of a spoken language system, and their normal development in fact crucially depends on the successful development of spoken language abilities, the general view was that written language does not have a system of its own. As a consequence, the majority of written language disorders was considered to be a consequence of the impairment of the system of spoken language (see De Bleser & Luzzatti, 1989 for a review). The only classical modality-specific impairment of written language was alexia, a total impairment of reading already affecting letter-level processing, with and without agraphia (see below). This view radically changed with the introduction of cognitive neuropsychological models of reading. These were based on models of normal reading that introduced the view that unimpaired readers of alphabetic scripts, in which the smallest written unit corresponds approximately to a phoneme, have at least two routines for deriving the phonology of written words: a lexical route, which allows the association of whole-word pronunciations from stored lexical knowledge to a sight vocabulary, and a nonlexical routine, in which phonemes corresponding to a word’s graphemes are sounded out one by one. Of importance for the dual-route model is the distinction between regular words and exception words. Regular words in reading comply to the

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grapheme-to-phoneme correspondence (GPC) rules of the language (e.g. EA pronounced as /i:/ as in speak or beak), whereas irregular/exception words deviate from these (e.g. EA pronounced as /ei/ as in steak). The proportion of exception words in reading varies among languages using an alphabetic script. It is low in Italian and German but high in English. Furthermore, there may be an asymmetry between reading and writing. Thus, there are few exception words for reading German and French, since GPCs are highly transparent, but the proportion is much higher in these languages for writing, where the relations between phonemes and graphemes are less transparent. For example, the German word Saal (room) can be read unambiguously by a sequential procedure using the correspondence rule AA → /a:/, but writing is ambiguous, since the phoneme-to-grapheme correspondence (PGC) rules provide three alternatives, Sahl, Saal, and Sal, only one of which is lexically correct. Thus, apart from chance, correct responses in writing require lexical processing in writing such words, though reading may be successful by using nonlexical sequential processing. Dual-route models of reading Figure 6.1 depicts a version of a dual-route model of reading. The ability a normal subject has to read regular nonlexical strings as well as words with irregular or unpredictable orthography (such as yacht, and pint, or the ambiguous pronunciation of the letter string EA in dear, bear, heart, or steak) can best be explained by assuming two complementary reading procedures, a sub-word-level route and a lexical route (Figure 6.1). The sub-word-level procedure takes the string of graphemes as its input and converts it into a string of phonemes by using sublexical GPC rules (orthographic-to-phonological conversion). This is the only possibility of reading nonwords, since they do not have a lexical entry. Furthermore, reliance on this route leads to the correct realization of words with regular GPC. However, words with irregular GPC lead to regularizations if read by this route (steak → /sti:k/). Their correct realization in reading aloud relies on reading via the lexical route. With this procedure, graphemic strings activate the graphemic word stored in long-term memory in the orthographic input lexicon, which, in turn, activates the corresponding phonological word as a whole in the phonological output lexicon. Activation of the phonological output word from the graphemic input word may be achieved by direct lexiconto-lexicon mapping, or indirectly if the graphemic lexicon first activates the relevant concept in the cognitive system, which then fires to the corresponding phonological entry in the output lexicon. The lexical procedure is mandatory for correctly reading irregular words, but it can also be used for the realization of regular words, which also have lexical entries. In normal reading, the three procedures work in parallel, and the one leading to the fastest output wins. However, for nonword reading, the sublexical route is obligatory whereas correct reading of irregular words requires lexical activation. All procedures

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Figure 6.1 Dual-route model of reading. Sub-word-level (sublexical) reading route: one-step orthographic-to-phonological conversion (grapheme-to-phoneme correspondence (GPC)). Whole-word (lexical) reading routes: (1) direct lexical route: directly from the orthographic (graphemic) input lexicon to the phonological output lexicon; (2) lexical-semantic route: indirectly from the orthographic input lexicon via the cognitive system (lexical semantics, conceptual knowledge) to the phonological output lexicon.

require a short-term deposit in the so-called phonemic/phonological buffer before articulation is executed. Obviously, buffer resources needed for sublexical reading are higher, given that a graphemic string results in the sum of the corresponding phonemes, whereas for lexical reading, the unit which the buffer needs for processing is the entire morpheme, and not the single phoneme. Since less familiar graphemic words and nonwords have to use the sublexical route for their realization, an interaction between lexical status and length

116 De Bleser and Luzzatti is predicted. Items in sight vocabulary should not be affected by letter length since the letters can be identified in parallel, whereas nonwords do not exist in sight vocabulary and should therefore be affected by length if phonics reflects serial processing. This is indeed what was observed by Weekes (1997), who showed longer reading reaction times to longer nonwords (7 letters) compared to shorter ones (3 letters), but not in the case of words. A further prediction of dual-route models is that normal readers should show an interaction between lexical factors such as word frequency and regularity. Paap and Noel (1991) demonstrated a regularity by frequency interaction in reaction times of normal readers. There was no difference in reaction times to high-frequency regular and exception words, which have a stable lexical representation, but there were significantly longer reaction times to low-frequency exception words than to low-frequency regular words. Based on such dual-route models, the prediction for conditions of brain damage is that there are different modality-specific disorders of graphemic processing that are not just a consequence of an aphasic disorder of the spoken language system; that is, they are not qualitatively similar to this disorder. In this view, acquired dyslexia refers to a group of organic impairments of different aspects of reading in cases where reading was acquired normally and visual perception is unimpaired. The reading impairment can be due to a loss of phonological recoding ( phonological dyslexia/ deep dyslexia; see below) resulting in the inability to read nonwords, or loss of direct lexical access (surface dyslexia, see below) characterized by difficulty in reading irregular/exception words. Dual-route models of spelling Following the dual-route models of reading, similar models were developed to account for normal writing skills (Figure 6.2). Once more, sublexical and lexical routes were postulated. The sublexical procedure takes the phonological string as its input and converts the product of auditory acoustic analysis into a corresponding graphemic string by means of PGC rules. In contrast to reading, where the sublexical conversion is a one-step procedure, the model for writing in Figure 6.2 adopts a two-step procedure: first auditory-to-phonology conversion with short-term deposit in the phonological output buffer, and then phonology-to-orthography conversion (phoneme-tographeme conversion), with subsequent short-term retention in the graphemic output buffer. This procedure is the only possible one if nonwords have to be written to dictation, and it can also be used in writing regular words. However, the correct spelling of irregular words is based on usage of the lexical route by means of either direct mapping between the phonological input and graphemic output lexicons, or indirectly mapping these two by first associating the conceptual meaning with the phonological input word and only then activating the graphemic word in the output lexicon. Of course, the lexical procedure can also be used for successful writing of regular words, since, like irregular words, they have lexical entries. As in reading, the lexical

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Figure 6.2 Dual-route model of spelling. Sub-word-level (sublexical) route of spelling: two-step (1) acoustic-to-phonological conversion (APC) and (2) phonemeto-grapheme conversion (PGC). Whole-word (lexical) spelling routes: (1) direct lexical route: directly from the phonological input lexicon to the graphemic (orthographic) output lexicon; (2) lexical-semantic route: indirectly from the phonological input lexicon via the cognitive system (lexical semantics, conceptual knowledge) to the graphemic output lexicon.

and sublexical procedure send their products to the graphemic output buffer, but resource requirements on this short-term memory system are much higher if it receives its input from the sublexical procedure in terms of graphemes rather than in terms of morphemes, as is done in the lexical procedure. The dual-route model of writing postulates that, like acquired dyslexia, acquired agraphia/dysgraphia similarly refers to a group of organic impairments affecting different aspects of the ability to write even though writing

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was acquired normally and hand motor skills are preserved. Problems may occur in writing nonwords when the sublexical PGC route is not available ( phonological dysgraphia/deep dysgraphia, see below) or in writing irregular words when direct lexical access has become impossible (surface dysgraphia; see below). There are a number of languages, such as Chinese or Japanese kanji, that have opted for a nonalphabetic (logographic) script; that is, one in which a symbol represents a word. Other languages, such as Arabic and Hebrew, use a consonantal script in which vowels are not realized. Given such variability among writing systems, the question is whether the models developed for alphabetic scripts are universally valid. We will return to this question in the discussion. In the following, we will restrict ourselves to examples from alphabetic writing systems.

Dyslexia Classical modality-specific impairment of graphemic processing: alexia with and without agraphia Déjerine (1892) developed an anatomofunctional model of reading and spelling involving a representation of the graphemic word (CVM (center of visual memories); Figure 6.3) in the angular gyrus. Wernicke (1886) had explicitly rejected this view. For him, only the single letters of the alphabet are psychologically real, but not the graphemic words. Déjerine’s model of graphemic processing became most influential because of his careful neuropsychological and neuroanatomical description of two patients suffering from isolated impairments of written language without concomitant aphasia: one patient had pure alexia without agraphia and another presented with alexia with agraphia. The lesion in Monsieur C with pure alexia involved the left occipital lobe, including the splenium of the corpus callosum. In the patient who also had agraphia, the lesion was confined to the left angular gyrus. This was taken to be the center containing representations of graphemic words (CVM). Visually processed letters in the left or the right occipital visual center (OVC) must access the CVM for graphemic word processing, and from there information is transmitted to the center of auditory memories (CAM), that is, Wernicke’s area, for further language processing. Reading aloud requires a further projection to the motor center of word articulation (MCA), that is, Broca’s area. For writing to dictation, the projection goes from the CAM to the CVM, and from there to the hand motor center (HMC), where the graphic motor patterns of letters are stored. From this model, it follows that a lesion in the CVM results in both alexia and agraphia, which is exactly what Déjerine found. If the CVM itself is preserved but dissociated from the OVCs, writing is still possible but there will be pure alexia. This corresponds to Déjerine’s anatomical findings for Monsieur C, whose brain showed

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Figure 6.3 Déjerine’s anatomical model of written language. CVM: center of visual memories; OVC: occipital visual centers; CAM: center of auditory memories (i.e. Wernicke’s area); MCA: motor center of word articulation (i.e. Broca’s area); HMC: hand motor center. Alexia with agraphia is caused by damage to the CVM, while pure alexia requires damage to the left OVC and isolation of the CVM from the contralateral right OVC (from Déjerine, 1914).

damage to the left OVC and an isolation of the CVM in the left hemisphere from the contralateral right OVC due to the splenial lesion of the corpus callosum. Déjerine’s view of graphemic processing became influential again in modern neurology after its resurrection by Geschwind (1965). Cognitive neuropsychological impairments of graphemic processing: varieties of dyslexia Deep dyslexia In deep dyslexia, patients read fluently but make semantic errors in reading words. In a simple test situation in which single words are presented for

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reading aloud without context and with unlimited view, responses occur that are related to the target in meaning but may be totally different graphemically and phonologically (Marshall & Newcombe, 1966, 1973). For example, deep dyslexics may read king as sovereign, boat as anchor, and skirt as dress. Such semantic errors are the cardinal feature of deep dyslexia, but other symptoms occur as well (see Coltheart, 1987, for a review). Nonwords (neologisms) such as ling or fullip cannot be read. Exception words and regular words lead to similarly incorrect responses. In addition to semantic errors, visual errors may occur in which target and response share a large number of letters (boat → brat). Furthermore, word reading is characterized by a concreteness effect such that concrete (highly imageable) words (tulip) are read better than abstract ones (idea). Function words such as and, the, and or are rarely read correctly, and they are at the bottom line in a part of speech effect (nouns > verbs > adjectives > function words). Writing is often impossible, but if the patient can write, there is often deep dysgraphia; that is, the writing shows similar symptoms to reading. Patients with deep dyslexia usually have an extensive left-hemisphere lesion leading to aphasia (usually Broca’s aphasia) and right hemiplegia. Notwithstanding the severity of the disorder, symptom-guided therapy of deep dyslexia has been demonstrated to be effective (de Partz, 1986). Surface dyslexia Patients with surface dyslexia can be either fluent or nonfluent readers. In contrast to patients with deep dyslexia, they are quite able to read nonwords but are impaired in reading exception words. In a simple testing situation, in which exception words have to be read aloud without context and with unlimited presentation time, so-called regularization errors occur; that is, words are pronounced according to the regular GPC rules. For example, dough may be read as rhyming with cough, and pint with hint. Exception words are read worse than regular words even when they are matched for word frequency, grapheme number, etc., and responses are produced that are phonologically similar to the target. Regularizations are the cardinal symptom of surface dyslexia, but other symptoms also occur (see Patterson, Marshall, & Coltheart, 1985, for a review). In particular, a length effect is often observed for regular words and nonwords such that stimuli with more graphemes lead to more errors than those with less graphemes. The patient’s writing is often also surface dysgraphic; that is, writing shows similar symptoms to reading. Surface dyslexia is often encountered in slowly progressive aphasia but has also been reported in aphasic patients with vascular etiology. Treatment of surface dyslexia has been shown to be effective if a mnemonic technique is used to repair the direct connection between graphemic words and the corresponding spoken words (Byng & Coltheart, 1986; Coltheart & Byng, 1989; Weekes & Coltheart, 1996).

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Phonological dyslexia Clinically, patients with phonological dyslexia often appear to be unimpaired, since they are able to read words fluently. The main symptom of phonological dyslexia is an impairment in reading nonwords, although this ability is usually not totally lost (for an exception, see Funnell, 1983). Reading exception words and regular words is relatively preserved, but there are no cases where word reading was 100% correct. There are many similarities between phonological dyslexia and deep dyslexia. In both cases, nonword reading is more severely impaired than word reading. The additional symptoms of deep dyslexia, such as the presence of a concreteness effect or a frequency effect, have also been observed in some cases of phonological dyslexia. Distinguishing characteristics are the occurrence of semantic errors and a total inability to read nonwords, which point to deep rather than phonological dyslexia. Little is known about the writing performance of phonological dyslectics and of the underlying anatomical lesion. Furthermore, there are presently no therapy studies on acquired phonological dyslexia, although successful therapy may be expected, since patients with the more severe symptoms of deep dyslexia have been shown to respond well to intensive treatment and regained the ability to read by the GPC reading routine. Letter-by-letter reading This refers to the oldest and clinically best-known form of acquired reading disorder, Déjerine’s alexia without agraphia, but it stresses the functional rather than the neuroanatomical analysis of the impairment. Patients have lost the ability to read words and nonwords. The single letters of the stimulus are named from left to right, and the patient may reach the target phonological string using a backward spelling strategy, but the procedure is slow and laborious, and the total stimulus reading time is linear, since it is the sum of the reading time for each letter. Patients can write spontaneously but are unable to read the text they produced after a few minutes. Many but not all published cases of letter-by-letter reading involve an occipital lesion extending to the splenium (posterior part) of the corpus callosum, as originally described by Déjerine. A lesion in the left occipital lobe not extending to the splenium provokes a right homonymous hemianopia, but no reading impairment for stimuli presented to the left visual field. Patients who have only right hemianopia can process stimuli via the left visual field (right-hemisphere visual cortex) and transmit this information via the splenium to the left hemisphere reading areas. However, if the splenium is disrupted, the transmission from right to left is impaired. The ability to read slowly in a letter-by-letter fashion probably expresses how the transfer to the left hemisphere proceeds when the normal transmission via the splenium is no longer available (Coslett & Saffran, 1989).

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Letter-by-letter reading sometimes recovers partly or in full during the first couple of weeks or months after the stroke. In chronic cases, successful treatment has been demonstrated (Moody, 1988; Moyer, 1979). Neglect dyslexia Neglect dyslexia is usually associated with general visuospatial unilateral neglect, in which case it does not represent a specific impairment of reading. In cases of unilateral neglect, the patient has a hemi-inattention and/or representational impairment on the side contralateral to the lesion, as a rule, the left side of a patient’s visual field, body, and extrapersonal space. In word reading, patients neglect the left part of the word, resulting in either omissions (dying for studying) or substitutions (window for meadow) (Arduino et al., 2002; Arguin & Bub, 1997). In sentence reading, they tend to ignore the words from the left to the middle. In rare cases, neglect dyslexia has been reported as a specific impairment without accompanying general neglect (e.g. Patterson & Wilson, 1990). In neglect dyslexia, there is no difference between processing words and nonwords. Reading is fluent, and it is correct if stimuli are presented vertically. There is no aphasia, and language comprehension and production are unimpaired. There may be associated neglect dysgraphia (Baxter & Warrington, 1983). The lesion underlying left neglect dyslexia is in the right hemisphere. In many cases, there is spontaneous recovery, but the impairment may be persistent. Therapy makes use of scanning cues such as red markings on the left side of the page, which are gradually blended out. Assessment of reading impairments Assessment material based on the dual-route model of reading has been developed for English (the Psycholinguistic Assessment of Language Processing in Aphasia (PALPA) test (Kay, Lesser, & Coltheart, 1992)). This test is available in German, Dutch, and Spanish translations. Such material typically includes a large number of tasks addressing each box and route of the model. For example, visual lexical decision of graphemic words and nonwords is used to examine the status of the graphemic input lexicon; reading aloud nonwords, to investigate the functioning of the GPC route; reading irregular words of different frequency levels, to determine whether the direct lexical route is accessible, etc. In the German test LeMo, developed by De Bleser et al. (2004), functional lesions in the model are automatically generated from the test results, and a comparison of the variables is included.

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Dysgraphia Classical modality-specific impairment of the spelling process In classical aphasiology, the possibility of modality-specific impairments of writing, so-called pure agraphia, was debated. Whereas Wernicke’s French contemporaries predicted and described motor aphasia of the hand (Charcot, 1883), or motor agraphia (Pitres, 1884) as a result of damage to orthographic representations, Wernicke (1903; see De Bleser, 1996) rejected the concept of a motor orthographic center and consequently also of pure agraphia. In his view, cases of “isolated” agraphia had to be the consequence of an undiagnosed aphasic disorder. The only agraphia without aphasia he accepted was alexia with agraphia (see previous discussion of alexia), that is, a modality-unspecific impairment of written language. Almost all classical authors had their own classification of agraphic disturbances with or without aphasia, leading more to confusion than to interest in the topic, but they usually agreed on one form, apraxic agraphia. Apraxia of writing is characterized by the patient’s inability to realize letter symbols due to ideokinetic or constructional factors. If the former predominate, letter symbols cannot be realized graphically, and individual letter strokes cannot be combined adequately. In this type of dysgraphia oral spelling and typing on a keyboard are unimpaired. If constructional factors are predominant, there may be an impairment in retrieving the spatial aspects of letter forms from memory. However, the disorder cannot be traced back to a general ideomotor or constructional apraxic deficit, since there can be apraxic agraphia without any other major apraxic impairment, and the reverse. Cognitive neuropsychological impairments of the spelling processes Interest in writing disorders reappeared after the introduction of dual-route models of spelling, constructed in analogy to the dual-route models of reading. Empirical evidence was obtained from aphasic patients with subtotal impairments of writing (dysgraphia) who showed a variety of patterns of acquired spelling disorders qualitatively different from the aphasic and, in some cases, dyslexic disorders (Beauvois & Dérouesné, 1981; Patterson, 1986; Shallice, 1981). Varieties of dysgraphia As in dyslexia, the dysgraphic disorder may reflect an impairment of the lexical or sublexical writing procedure. Impairment of the lexical procedure results in surface dysgraphia, which is characterized by preserved writing of nonwords and words with regular PGC but regularization of irregular words. Impairment of the sublexical route results in the superiority of word over nonword writing, and a length effect may be expected in spelling nonwords.

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In phonological dysgraphia, regular and irregular words are spelled relatively well, especially if they are of high frequency, but spelling of nonwords is impaired. Like deep dyslexia, deep dysgraphia is mainly characterized by semantic errors in writing words and the inability to spell nonwords. A post-lexical impairment may occur at the level of the graphemic buffer. This will express itself in graphemic substitutions, generally respecting the orthosyllabic structure of the target; that is, vowels are substituted for vowels, consonants for consonants, and consonant clusters for clusters. Given that requirements for buffer resources are higher for nonwords than words, nonwords are more affected. Ellis (1988) suggested that after the graphemic level there is a peripheral, allographic level that is sensitive to different letter case and shape. An impairment at this level will usually be restricted to handwriting. Two adjacent letters may be mixed; typically, the patient confuses upper and lower case. In contrast to apraxic agraphia (see above), patients with allographic dysgraphia write fluently with well-formed letter shapes. Specific treatment of acquired spelling impairments has not always been successful. Model-oriented rehabilitation of dysgraphia seems to be most effective (1) in languages with shallow orthography, (2) when the spelling impairment is treated by the sub-word-level routine, and (3) when it involves not only the phonology-to-orthography but also the auditory-to-phonology conversion process (Luzzatti, Colombo, Frustaci, & Vitolo, 2000). Assessment of spelling impairments In analogy to assessment material for reading, writing tasks have been developed based on the dual-route model (the PALPA test by Kay et al., 1992; the Johns Hopkins University Dysgraphia Battery by Goodman & Caramazza, 1986). They include writing to dictation of nonwords of different length to examine the PGC route and the graphemic buffer, writing regular and irregular words of different frequency to investigate the lexical route, written naming to examine the semantic route. For post-lexical processing, letter transposition tasks are often included.

Conclusion Dual-route models of written word processing have become paradigm cases for cognitive science and have been very successful in accounting for word and nonword reading and writing and their impairments. Although they were originally based on English, research has meanwhile been conducted on other languages and orthographies. Data are now available on several other European languages based on alphabetic scripts (French, German, and Italian), consonantal scripts (Hebrew), syllabic scripts (Japanese kana), and ideographic scripts (Chinese and Japanese kanji). Taken together, these studies point to the universality of two routes for reading, a lexical and a sublexical one, applying to nonalphabetic as well as alphabetic languages, and each

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route can be selectively impaired, thus suggesting their independent neural organization (Butterworth & Yin, 1991; Weekes, 2005). At the same time, neuroimaging studies of subjects in different alphabetic languages with a different degree of transparency between graphemes and phonemes suggest that a greater reliance on one or the other route depends on language-specific features (Paulesu et al., 2001). Given the similarity between languages with respect to the architecture of the model, future research can now focus on the role of specific differences.

References Arduino, L. S., Burani, C., & Vallar, G. (2002). Lexical effects in neglect dyslexia: A study in Italian patients. Cognitive Neuropsychology, 19, 421–444. Arguin, M., & Bub, B. (1997). Lexical constraints on reading accuracy in neglect dyslexia. Cognitive Neuropsychology, 14, 765–800. Baxter, D. M., & Warrington, E. K. (1983). Neglect dysgraphia. Journal of Neurology, Neurosurgery, and Psychiatry, 45, 1073–1078. Beauvois, M. F., & Dérouesné, J. (1981). Lexical or orthographic agraphia. Brain, 104, 21–49. Butterworth, B., & Yin, W. G. (1991). The universality of two routines for reading: Evidence from Chinese dyslexia. Proceedings of the Royal Society of London. Series B., Biological Sciences, 246, 91–95. Byng, S., & Coltheart M. (1986). Aphasia therapy research: Methodological requirements and illustrative results. In I. G. Nilsson & E. Hjelmquist (Eds.), Communication and handicap: Aspects of psychological compensation and technical aids (pp. 191–213). Amsterdam: North-Holland Publishing. Charcot, J.-M. (1883). Le differenti forme di afasia. Milan: Vallardi. Coltheart, M. (1987). Deep dyslexia: A review of the syndrome. In M. Coltheart, K. Patterson & J. C. Marshall, (Eds), Deep dyslexia (2nd ed., pp. 22–47). London: Routledge and Kegan Paul. Coltheart, M., & Byng, S. (1989). A treatment for surface dyslexia. In X. Seron (Ed.), Cognitive approaches in neuropsychological rehabilitation (pp. 159–174). London: Lawrence Erlbaum Associates Ltd. Coslett, H. B., & Saffran, E. M. (1989). Evidence for preserved reading in ‘pure alexia’. Brain, 112, 327–359. De Bleser, R. (1996). Wernicke’s 1903 case of pure agraphia: An enigma for classical models of written language processing. In Ch. Code, C. W. Wallesch, A. R. Lecours, & Y. Joanette (Eds), Classic cases in neuropsychology (pp. 13–29). Hove: Lawrence Erlbaum Associates Ltd. De Bleser, R., Cholewa, J., Stadie, N., & Tabatabaie, S. (2004). LeMo Lexikon modellorientiert: Einzelfalldiagnostik bei Aphasie, Dyslexie und Dysgraphie. Amsterdam: Elsevier. De Bleser, R., & Luzzatti, C. (1989). Models of reading and writing and their disorders in classical German aphasiology. Cognitive Neuropsychology, 6, 501–513. Déjerine, J. (1892). Contribution à l’étude anatomo-pathologique et clinique des différentes variétés de cécité verbale. Mémoires de la Société de Biologie, 4, 61–90. Déjerine, J. (1914). Séméiologie des affections du système nerveux. Paris: Masson. De Partz, M. P. (1986). Re-education of a deep dyslexic patient: Rationale of the method and results. Cognitive Neuropsychology, 3, 149–177.

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Ellis, A. W. (1988). Modelling the writing process. In G. Denes, C. Semenza, & P. Bisiacchi, (Eds.), Perspectives on cognitive neuropsychology (pp. 189–213). Hove: Lawrence Erlbaum Associates Ltd. Funnell, E. (1983). Phonological processes in reading: New evidence from acquired dyslexia. British Journal of Psychology, 74, 159–180. Geschwind, N. (1965). Disconnection syndromes in animals and men. Brain, 88, 237–294; 585–644. Goodman, R., & Caramazza, A. (1986). The Johns Hopkins University Dysgraphia Battery. Baltimore, MD: Johns Hopkins University Press. Kay, J., Lesser, R., & Coltheart, M. (1992). Psycholinguistic assessments of language processing in aphasia (PALPA). Hove: Lawrence Erlbaum Associates Ltd. Luzzatti, C., Colombo, C., Frustaci, M., & Vitolo, F. (2000). Rehabilitation of spelling along the sub-word-level routine. Neuropsychological Rehabilitation, 10, 249–278. Marshall, J. C., & Newcombe, F. (1966). Syntactic and semantic errors in paralexia. Neuropsychologia, 4, 169–176. Marshall, J. C., & Newcombe, F. (1973). Patterns of paralexia: A psycholinguistic approach. Journal of Psycholinguistic Research, 2, 175–199. Moody, S. (1988). The Moyer reading technique re-evaluated. Cortex, 24, 473–476. Moyer, S. B. (1979). Rehabilitation of alexia: A case study. Cortex, 15, 139–144. Nelson, H. E. (1982). National Adult Reading Test Manual. Windsor: NFER-Nelson. Paap, K. R., & Noel, R. W. (1991). Dual-route models of print to sound: Still a good horse race. Psychological Research, 53, 13–24. Patterson, K. (1986). Lexical but nonsemantic spelling? Cognitive Neuropsychology, 3, 341–367. Patterson, K., Marshall, J. C., & Coltheart, M. (Eds.) (1985). Surface dyslexia: Cognitive and neuropsychological studies of phonological reading. Hove: Lawrence Erlbaum Associates Ltd. Patterson, K., & Wilson, B. A. (1990). A rose is a rose or a nose: A deficit in initial letter recognition. Cognitive Neuropsychology, 7, 447–477. Paulesu, E., Démonet, J. F., Fazio, F., McCrory, E., Chanoine, V., Brunswick, N., et al. (2001). Dyslexia—cultural diversity and biological unity. Science, 291, 2165–2167. Pitres, A. (1884). Considérations sur l’agraphie à propos d’une observation nouvelle d’agraphie motrice pure. Revue de Médecine, 4, 855–873. Shallice, T. (1981). Phonological agraphia and the lexical route in writing. Brain, 104, 413–429. Shallice, T., & Warrington, E. K. (1980). Single and multiple component central dyslexic syndromes. In M. Coltheart, K. Patterson, & J. C. Marshall (Eds.), Deep dyslexia (pp. 119–145). London: Routledge and Kegan Paul. Weekes, B. S. (1997). Differential effects of number of letters on word and non-word naming latency. Quarterly Journal of Experimental Psychology, 50A, 439–456. Weekes, B. S. (2005). Acquired disorders of reading and writing: Cross-script comparisons. Behavioural Neurology, 16, 51–57. Weekes, B. S., & Coltheart, M. (1996). Surface dyslexia and surface dysgraphia: Treatment studies and their theoretical implications. Cognitive Neurospsychology, 13, 277–315. Wernicke, C. (1886). Die neueren Arbeiten über Aphasie. Fortschritte der Medizin, 4, 463–482. Wernicke, C. (1903). Ein Fall von isolierter Agraphie. Monatsschrift für Psychiatrie und Neurologie, 13, 241–265.

7

Developmental dyslexia From neuropsychology to genetics, and back again Albert M. Galaburda, Joseph LoTurco, and Glenn D. Rosen

It is becoming possible to establish links between gene dysfunction and neuropsychological symptoms; this is not the same as discovering the genetics of complex behaviors, but it is a start. Developmental dyslexia is the most common specific learning disorder in children, yet its underlying causes have escaped full understanding. Neurophysiological and neuroanatomical findings indicate that dyslexia is associated with alterations in both neocortical function and structure (Brambati et al., 2004; Galaburda & Livingstone, 1993; Paulesu et al., 2001; Siok, Perfetti, Jin, & Tan, 2004). The pattern and timing of such neurobiological changes suggest that developmental dyslexia may be caused in part by alterations in early brain development and neuronal migration (Brambati et al., 2004; Galaburda, Sherman, Rosen, Aboitiz, & Geschwind, 1985). In addition to neurobiological correlates, there is substantial evidence that dyslexia susceptibility associates with multiple genetic loci (Fisher & DeFries, 2002; Grigorenko, 2003). In the present review, presented in honor of Luigi Vignolo for his outstanding contributions to neuropsychology, we will outline the main steps between a proposed genetic mutation or variant and a neuropsychological deficit that often accompanies developmental dyslexia—abnormal auditory processing. The chapter summarizes a journey that began with learning about the neuropsychological, behavioral, and cognitive disorder we call developmental dyslexia; continued with an attempt to describe its neurological underpinning; and finally ended with the discovery of the genetic mechanism leading to anomalous brain development affecting areas involved in the neuropsychological functions of interest.

Genetic background Dyslexia susceptibility loci have been shown to be present on the X chromosome as well as autosomal chromosomes 1, 2, 3, 6, 11, 15, and 18 (de Kovel et al., 2004; Fisher & DeFries, 2002; Grigorenko, 2003; Scerri et al., 2004; Taipale et al., 2003; Wigg et al., 2004), and the first candidate dyslexia susceptibility gene, DYX1C1 (also known as EKN1), is located on 15q21 (Taipale et al., 2003; Wigg et al., 2004). In utero interference (RNAi) with the

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translation of DYX1C1 protein disrupts both the migration and morphology of developing neurons (Wang et al., 2004). Cellular and biochemical experiments indicate that DYX1C1 functions within the cytoplasm of migrating neurons, interacts with the neuronal migration gene LIS1, and regulates the association of LIS1 with the cell motor protein dynein. These results have established DYX1C1 as a novel neuronal migration protein, and have linked dyslexia susceptibility to molecular mechanisms underlying neocortical development. The results also suggest that the disorder of neurodevelopment and migration associated with dyslexia is only one possible outcome in a range of mild to severe disturbances of cortical development related to altered genes involved in neuronal migration, which also includes lissencephaly type I. Given the growing number of genes discovered to be involved in neuronal migration and cortical development, an important aim of current and future studies is to determine whether proteins coded by genes within other dyslexia susceptibility loci play similar roles in neuronal migration and development.

Neuroanatomical background Abnormal migration secondary to developmental genes such as DYX1C1 is capable of triggering a cascade of anatomical changes likely to be responsible for the cognitive and behavioral deficits seen in developmental dyslexia. Work on the mechanisms of function of the altered DYX1C1 gene indicates that the gene has both cell-autonomous and non-cell-autonomous effects on cortical development (Wang et al., 2004). Thus, while cell-autonomous mechanisms explain the abnormal interactions between young neurons and the radial glia along which they must migrate to the incipient cerebral cortex, and the resultant periventricular migrational arrest, additional non-cell-autonomous effects lead to focal disorganization of the layering of neurons in the developing cortex. Other non-cell-autonomous effects may lead to breaches in the external glial limiting membrane, resulting in the production of layer I ectopic collections of neurons and glia (ectopia) (Galaburda et al., 1985) (Figure 7.1). Experimental induction of ectopia by physical means in rats or mice, such as by freezing injury to the surface of the cortex at postnatal day 0 or 1 (P0, P1), can reproduce these same effects and lead to layer I ectopia and focal areas of microgyria in the affected cortex (Humphreys, Rosen, Press, Sherman, & Galaburda, 1991; Rosen, Sherman, Richman, Stone, & Galaburda, 1992). Induction of ectopia by physical means, which themselves are quite insignificant in size, triggers changes of a widespread nature in other areas of the cerebral cortex as well as in the thalamus (Figure 7.2), which is thought to be the actual mechanism underlying the functional changes. These changes include alterations in the types and proportions of neuronal types and in patterns of neural connections (Herman, Galaburda, Fitch, Carter & Rosen, 1997; Rosen, Burstein, & Galaburda, 2000; Rosen, Herman, & Galaburda, 1999; Rosen, Jacobs, & Prince, 1998; Sherman, Stone, Press, Rosen, &

Figure 7.1 Brightfield photomicrograph of ectopic collections of neurons in the molecular layer of the cortex of a rat (left) and human dyslexic patient (right). In the case of the rat, cortical neurons were embryonically transfected with shRNA targeted against the candidate dyslexia susceptibility gene Dyx1c1. Bar = 250 µm.

Figure 7.2 Fluorescence photomicrograph of Fluoro-Jade B-stained neurons in the ventrobasal complex of the rat thalamus following induction of microgyria in the newborn cerebral cortex. Cell death is felt to be the principal mechanism by which proportions of neuronal types in the thalamus change in cortical malformations.

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Galaburda, 1990). Evidence exists of decreased cortical inhibition in affected cortical areas (Jacobs, Gutnick, & Prince, 1996; Jacobs & Prince, 2005) and of anomalous connections between injured cortex, adjacent cortex, and even homotopic and nonhomotopic cortex in the contralateral hemisphere (Rosen et al., 2000). With respect to the thalamus, abnormal afferent and efferent connections between the injured cortex and thalamus result from the induction of cortical ectopia (Rosen et al., 2000). There are changes in the numbers of large and small neurons in specific thalamic sensory nuclei, even when they do not directly project to the area of affected cortex (Herman et al., 1997). The cellular changes are associated with deficits in auditory processing (see below). In the lateral geniculate nucleus, the average size of neurons in the magnocellular layers was found to be reduced by 30% in the brains of dyslexic individuals (Livingstone, Rosen, Drislane, & Galaburda, 1991). In the medial geniculate nuclei, dyslexic human brains showed a shift to smaller neurons, and this again could be produced in experimental animals by induction of focal cortical malformations by freezing injury at P0 (Fitch, Tallal, Brown, Galaburda, & Rosen, 1994; Herman et al., 1997). Of additional interest was the finding that, despite comparable severity of the cortical injury and resultant cortical malformation, female rats, unlike their male counterparts, did not develop the predicted changes in thalamic neurons (Herman et al., 1997). This indicated that females are more resistant than male rats to the secondary changes in the thalamus that result from induction of cortical malformations at birth. However, the pattern of male reaction to cortical injury could be induced in the females when the latter were exposed to the male sex hormone testosterone (Herman et al., 1997).

Behavioral consequences In alphabetic languages, phonological problems describe the majority of children with developmental dyslexia (Lyon, 1996). This is usually demonstrated by tests addressing conscious awareness of the phonological structure of words, such as rhyming or phoneme deletion tasks and pig Latin games. The origin of these metaphonological deficits is not known, but some experts believe that they result from abnormal auditory perceptual processing during critical stages of phonological development early in childhood (Benasich, 2002; Tallal, 1976; Tallal, Stark, & Mellits, 1985). A variety of temporal auditory processing problems have been reported, some that concern rapid sound changes, and others involving slow auditory transitions (review and critique by Ramus; see Galaburda & Cestnick, 2003). Behavioral and cognitive aberrations can also be demonstrated by functional imaging methods, such as PET and fMRI. The application of these tools often discloses differences in activation of cortical areas between good and poor readers, which involve perisylvian cortices, inferior prefrontal regions, temporoparietal junction cortex, and the “word-form” area located at the border between the temporal and occipital lobes on the left side

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(Dehaene, Le Clec’H, Poline, Le Bihan, & Cohen, 2002; Demonet, Taylor, & Chaix, 2004; Pugh et al., 2000). These are also areas where ectopia has been shown to be present in dyslexic brains (Galaburda & Cestnick, 2003; Galaburda et al., 1985). In languages such as Chinese, the details of the dysfunctional activation may differ in quite an interesting way, reflecting a different relationship between the orthographic code and semantics (Berman, Berger, Mukherjee, & Henry, 2004; Siok et al., 2004). Induction of cortical malformations in neonatal rats leads to temporal processing auditory deficits similar to some described in children with developmental language impairment. Affected animals show difficulty in processing rapidly changing sounds, as can be demonstrated in operant conditioning, oddball, and evoked potential paradigms (Clark, Rosen, Tallal, & Fitch, 2000; Fitch et al., 1994; Herman et al., 1997; Peiffer, Friedman, Rosen, & Fitch, 2004; Peiffer, Rosen, & Fitch, 2002; Rosen et al., 1999; Rosen, Waters, Galaburda, & Denenberg, 1995). Of further interest is the finding that only animals with induced cortical malformations that also demonstrate changes in the thalamus exhibit the temporal processing deficits, and this group comprises only males, the females being resistant to thalamic changes. Exposure of pregnant dams to testosterone leads to females acquiring thalamic changes, like the males, and, also like the males, temporal processing deficits. Therefore, the temporal processing deficits are linked to the secondary thalamic changes rather than to the initial cortical malformation.

Pathway: from gene to behavior Several susceptibility loci on the human genome have been linked to the phenotype of dyslexia, but only one candidate gene has been identified and studied so far. At the same time, several forms of developmental dyslexia must exist, affecting different components of language processing and perhaps also nonlinguistic abilities involved in reading. Of the Western form of dyslexia, the phonological type is the most common, and a tentative pathway now exists that can explain the phonological core deficit beginning with a gene mutation. Thus, we propose the following developmental scenario to explain phonological dyslexia in people who carry the DYX1C1 mutation or variant or another mutation affecting neuronal migration and cortical development in a comparable manner. Initially, there is a mutation in a gene crucial for proper neuronal migration and cortical development, such as DYX1C1. A mutation in such a gene leads to cell-autonomous and non-autonomous neuronal migration problems. These may begin with subventricular neuronal migration arrest, some of which may not be demonstrable later in life because of the shortened survival of subventricular, poorly migrated neurons. The abnormal process of neuronal migration, because of secondary effects on the health and integrity of radial glia, may also end with disruptions in cortical layering and ruptures in

132 Galaburda, LoTurco, Rosen the external glial limiting membrane (which is made up of the foot processes of radial glia). The latter changes comprise the main anomaly in cortical development as it concerns dyslexia, which includes the generation of layer I ectopia. Either the generation of ectopia or the underlying cortical changes lead to changes in cortico-cortical and corticothalamic connections, which in turn produce secondary cell changes in the thalamus. These thalamic cell and connectional changes lead to problems with auditory temporal processing, which in turn disrupt development of normal phonological representations and processes during language development. In turn, weakness or anomaly of phonological processing results in problems with phoneme-to-grapheme mapping—the core problem in developmental dyslexia.

Lingering questions Although a rough pathway can be drawn between a mutation or variant in a neuronal migration and development gene and a complex behavior such as phonological dyslexia, there are several areas where additional information is still needed. Several chromosomal locations may independently be responsible for genetic subphenotypes. This may affect people unevenly according to ethnic/ genetic background, as one may account for most dyslexics in one geographic or ethnic group but a few cases in another. We have already seen this phenomenon with regard to DYX1C1, where involvement of Finnish dyslexics is different from dyslexics in the UK or in Canada (Scerri et al., 2004; Wigg et al., 2004). The question remains as to whether the different genes are all neuronal migration genes, or whether they affect cortical development by interfering with different developmental molecular pathways, either pre- or post-migrationally. We have inconclusive evidence for the statement that neuronal migrational errors lead to non-cell-autonomous changes in layering and ectopia formation in the overlying cortex. Additional work needs be done to specify the steps by which secondary cortical malformations follow the impairment of subcortical neuronal migration directly linked to the gene mutation. Another set of questions relates to the exact mechanisms, described at cell biological and molecular levels, of the abnormalities in corticothalamic interactions felt to be crucial in the proposed step for abnormal phonological development. We do not yet know which signals are involved in transforming a cortical injury into an abnormal thalamus. Changes in programmed cell death are probably involved, but more data are needed to rule in or out other contributors. Yet another outstanding question has to do with the variation that may exist in the anatomical underpinnings of dyslexia. The only neuronatomical studies published thus far have been done in Western individuals, most likely suffering from phonological dyslexia. Other forms of dyslexia in Western languages (surface, deep), and dyslexia in nonsyllabic languages such as

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Chinese, may in fact be associated with different neuroanatomical substrates, which need to be characterized. The possibility that some aspects of the dyslexic phenotype are learned, rather than acquired in utero, suggests that brains will be found with functional anomalies not caused by underlying neuroanatomical defects. Modern neuroimaging tools will permit the discovery of such cases, and further developments in in vivo imaging will disclose details of the underlying neuroanatomy heretofore not possible to conceive. High-strength magnets and especially designed imaging protocols are even presently disclosing details of cortical anatomy previously only possible to see in postmortem or biopsy tissue (Berman et al., 2004; Maas et al., 2004). Nonetheless, it is clear that an important proportion of dyslexics do indeed have unusual brains from birth or before, which can be understood on the basis of comprehensible errors in cortical development beginning with a single gene mutation.

References Benasich, A. A. (2002). Impaired processing of brief, rapidly presented auditory cues in infants with a family history of autoimmune disorder. Developmental Neuropsychology, 22, 351–372. Berman, J. I., Berger, M. S., Mukherjee, P., & Henry, R. G. (2004). Diffusion-tensor imaging-guided tracking of fibers of the pyramidal tract combined with intraoperative cortical stimulation mapping in patients with gliomas. Journal of Neurosurgery, 101, 66–72. Brambati, S. M., Termine, C., Ruffino, M., Stella, G., Fazio, F., Cappa, S. F., et al. (2004). Regional reductions of gray matter volume in familial dyslexia. Neurology, 63, 742–745. Clark, M. G., Rosen, G. D., Tallal, P., & Fitch, R. H. (2000). Impaired processing of complex auditory stimuli in rats with induced cerebrocortical microgyria: An animal model of developmental language disabilities. Journal of Cognitive Neuroscience, 12, 828–839. Dehaene, S., Le Clec’H, G., Poline, J. B., Le Bihan, D., & Cohen, L. (2002). The visual word form area: A prelexical representation of visual words in the fusiform gyrus. Neuroreport, 13, 321–325. de Kovel, C. G., Hol, F. A., Heister, J. G., Willemen, J. J., Sandkuijl, L. A., Franke, B., et al. (2004). Genomewide scan identifies susceptibility locus for dyslexia on Xq27 in an extended Dutch family. Journal of Medical Genetics, 41, 652–657. Demonet, J. F., Taylor, M. J., & Chaix, Y. (2004). Developmental dyslexia. Lancet, 363, 1451–1460. Fisher, S. E., & DeFries, J. C. (2002). Developmental dyslexia: Genetic dissection of a complex cognitive trait. Review of Neuroscience, 3, 767–780. Fitch, R. H., Tallal, P., Brown, C. P., Galaburda, A. M., & Rosen, G. D. (1994). Induced microgyria and auditory temporal processing in rats: A model for language impairment? Cerebral Cortex, 4, 260–270. Galaburda, A. M., & Cestnick, L. (2003). Developmental dyslexia. Revue Neurologie, 36 (Suppl. 1), S3–9. Galaburda, A., & Livingstone, M. (1993). Evidence for a magnocellular defect

134

Galaburda, LoTurco, Rosen

in developmental dyslexia. Annals of the New York Academy of Sciences, 682, 70–82. Galaburda, A. M., Sherman, G. F., Rosen, G. D., Aboitiz, F., & Geschwind, N. (1985). Developmental dyslexia: Four consecutive patients with cortical anomalies. Annals of Neurology, 18, 222–233. Grigorenko, E. L. (2003). The first candidate gene for dyslexia: Turning the page of a new chapter of research. Proceedings of the National Academy of Sciences of the USA, 100, 11190–11120. Herman, A. E., Galaburda, A. M., Fitch, R. H., Carter, A. R., & Rosen, G. D. (1997). Cerebral microgyria, thalamic cell size and auditory temporal processing in male and female rats. Cerebral Cortex, 7, 453–464. Humphreys, P., Rosen, G. D., Press, D. M., Sherman, G. F., & Galaburda, A. M. (1991). Freezing lesions of the developing rat brain: A model for cerebrocortical microgyria. Journal of Neuropathology and Experimental Neurology, 50, 145–160. Jacobs, K. M., Gutnick, M. J., & Prince, D. A. (1996). Hyperexcitability in a model of cortical maldevelopment. Cerebral Cortex, 6, 514–523. Jacobs, K. M., & Prince, D. A. (2005). Excitatory and inhibitory postsynaptic currents in a rat model of epileptogenic microgyria. Journal of Neurophysiology, 93, 687–696. Livingstone, M. S., Rosen, G. D., Drislane, F. W., & Galaburda, A. M. (1991). Physiological and anatomical evidence for a magnocellular defect in developmental dyslexia. Proceedings of the National Academy of Sciences of the USA, 88, 7943–7947. Lyon, G. R. (1996). Learning disabilities. Future Child, 6, 54–76. Maas, L. C., Mukherjee, P., Carballido-Gamio, J., Veeraraghavan, S., Miller, S. P., Partridge, S. C., et al. (2004). Early laminar organization of the human cerebrum demonstrated with diffusion tensor imaging in extremely premature infants. NeuroImage, 22, 1134–1140. Paulesu, E., Demonet, J. F., Fazio, F., McCrory, E., Chanoine, V., Brunswick, N., et al. (2001). Dyslexia: Cultural diversity and biological unity. Science, 291, 2165–2167. Peiffer, A. M., Friedman, J. T., Rosen, G. D., & Fitch, R. H. (2004). Impaired gap detection in juvenile microgyric rats. Brain Research and Developmental Brain Research, 152, 93–98. Peiffer, A. M., Rosen, G. D., & Fitch, R. H. (2002). Rapid auditory processing and MGN morphology in microgyric rats reared in varied acoustic environments. Brain Research and Developmental Brain Research, 138, 187–193. Pugh, K. R., Mencl, W. E., Jenner, A. R., Katz, L., Frost, S. J., Lee, J. R., et al. (2000). Functional neuroimaging studies of reading and reading disability (developmental dyslexia). Mental Retardation and Developmental Disabilities Research Review, 6, 207–213. Rosen, G. D., Burstein, D., & Galaburda, A. M. (2000). Changes in efferent and afferent connectivity in rats with induced cerebrocortical microgyria. Journal of Comparative Neurology, 418, 423–440. Rosen, G. D., Herman, A. E., & Galaburda, A. M. (1999). Sex differences in the effects of early neocortical injury on neuronal size distribution of the medial geniculate nucleus in the rat are mediated by perinatal gonadal steroids. Cerebral Cortex, 9, 27–34. Rosen, G. D., Jacobs, K. M., & Prince, D. A. (1998). Effects of neonatal freeze lesions on expression of parvalbumin in rat neocortex. Cerebral Cortex, 8, 753–761.

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Rosen, G. D., Sherman, G. F., Richman, J. M., Stone, L. V., & Galaburda, A. M. (1992). Induction of molecular layer ectopias by puncture wounds in newborn rats and mice. Brain Research and Developmental Brain Research, 67, 285–291. Rosen, G. D., Waters, N. S., Galaburda, A. M., & Denenberg, V. H. (1995). Behavioral consequences of neonatal injury of the neocortex. Brain Research, 681, 177–189. Rosen, G. D., Windzio, H., & Galaburda, A. M. (2001). Unilateral induced neocortical malformation and the formation of ipsilateral and contralateral barrel fields. Neuroscience, 103, 931–939. Scerri, T. S., Fisher, S. E., Francks, C., MacPhie, I. L., Paracchini, S., Richardson, A. J., et al. (2004). Putative functional alleles of DYX1C1 are not associated with dyslexia susceptibility in a large sample of sibling pairs from the UK. Journal of Medical Genetics, 41, 1–5. Sherman, G. F., Stone, J. S., Press, D. M., Rosen, G. D., & Galaburda, A. M. (1990). Abnormal architecture and connections disclosed by neurofilament staining in the cerebral cortex of autoimmune mice. Brain Research, 529, 202–207. Siok, W. T., Perfetti, C. A., Jin, Z., & Tan, L. H. (2004). Biological abnormality of impaired reading is constrained by culture. Nature, 431, 71–76. Taipale, M., Kaminen, N., Nopola-Hemmi, J., Haltia, T., Myllyluoma, B., Lyytinen, H., et al. (2003). A candidate gene for developmental dyslexia encodes a nuclear tetratricopeptide repeat domain protein dynamically regulated in brain. Proceedings of the National Academy of Sciences of the USA, 100, 11553–11558. Tallal, P. (1976). Rapid auditory processing in normal and disordered language development. Journal of Speech and Hearing Research, 19, 561–571. Tallal, P., Stark, R. E., & Mellits, D. (1985). The relationship between auditory temporal analysis and receptive language development: Evidence from studies of developmental language disorder. Neuropsychologia, 23, 527–534. Wang, Y., Paramasivan, M., Thomas, A., Bai, J., Kaminen-Ahola, N., Kere, J., et al. (2004). Regulation of neuronal migration by DYX1C1. Submitted for publication. Wigg, K. G., Couto, J. M., Feng, Y., Anderson, B., Cate-Carter, T. D., Macciardi, F., et al. (2004). Support for EKN1 as the susceptibility locus for dyslexia on 15q21. Molecular Psychiatry, 9, 1111–1121.

8

Aphasia recovery Neural mechanisms Stefano F. Cappa and Jubin Abutalebi

Recovery of aphasia has been a central topic of Luigi Vignolo’s research. In his early paper on the evolution of aphasia and language rehabilitation, Vignolo (1964) clearly indicated some “principles” that would be confirmed by later research, such as that “the receptive aspect tends to improve more than the expressive aspect” and that “improvement of oral expression is not influenced by the initial level of auditory comprehension”. Given the relatively long history of research in this area, it is somewhat disappointing that the neural mechanisms underlying the spontaneous recuperation of aphasia, as well as, in general, the recovery of neurological function after acute brain injury, remain incompletely understood. Even less is known about the neural basis of the effects of therapeutic interventions aiming to rehabilitate neurological dysfunction. Much of recent research on the neural mechanisms underlying recovery is based on the assumption that the brain, rather than a static entity, is a constantly changing organ. Brain plasticity can be studied at various levels, from observable behavioral changes to cerebral maps, and from synaptic organization to molecular structures. Changes of cerebral maps after brain injury and functional recovery of lost functions may be studied in vivo with functional neuroimaging. These methods can be employed to explore what happens in the brain of aphasic patients after their stroke, and to track the modifications of brain function that may be correlated to recovery. In the present chapter, we will describe the functional neuroimaging evidence of cerebral reorganization, associated with both spontaneous and rehabilitation-induced improvement of language function.

Brain mechanisms involved in language recovery It has been repeatedly observed that, in general, language recovery occurs during the first months after the clinical onset of aphasia, the greatest improvement taking place during the first 3 months (Kertesz, Lesk, & McCabe, 1977; Sarno & Levita, 1971). The degree of functional improvement generally decreases over time. However, a lesser degree of recovery may still be observed 2 years after onset. The recovery period has often been divided into at least

138 Cappa and Abutalebi three stages, referring to the supposedly different pathophysiological mechanisms underlying clinical improvement. The three-epoch, time-frame model of aphasia recovery (Alexander, 1989; Mazzocchi & Vignolo, 1979) divides the clinical stages of aphasia into an early stage (lasting for about 2 weeks post-onset), a lesion stage (up to 6 months post-onset), and a chronic stage (after 6 months). The length of the period of “spontaneous recovery” varies, according to different authors, from the first weeks to first months after onset. Further improvement is likely to be more specifically related to language therapy. The difficulty in establishing an early prognosis is related to the contribution of different mechanisms to clinical recovery, both at the cognitive and at the anatomofunctional level. Many group studies on the prognosis of aphasic patients have indicated that the severity of the initial cognitive impairment (Pedersen, Jorgensen, Nakayama, Raaschou, & Olsen, 1995) and the volume of cerebral tissue loss (Mahagne et al., 2000) are negatively correlated with outcome. The availability of new magnetic resonance imaging (MRI) techniques, characterized by improved pathological specificity, now allows a more accurate estimate of the effects of the lesion characteristics on the recovery process. Indeed, good neurological recovery 2 months post-onset has been associated with the volume of tissue showing low blood flow and high oxygen extraction fraction (penumbra) at the acute stage that does not progress to complete infarction (Furlan, Marchal, Viader, Derlon, & Baron, 1996). One possible explanation is that penumbral tissue near the infarct is not viable early after injury and therefore cannot be recruited to support behavior. In the course of recovery, this tissue may return to a normal metabolic state and become functionally relevant to the substitution of the infarcted areas for task performance. However, in each individual case, the respective contribution of these mechanisms to the functional restoration of language and communication remains largely undetermined. During the early period, other mechanisms at the anatomofunctional level that might contribute to clinical improvement are the disappearance of cerebral edema and intracranial hypertension, the reabsorption of blood, the normalization of the hemodynamic situation in ischemic penumbra areas, and the resolution of local inflammation. All these factors may restore the excitability of the neurons, the functionality of local circuits, and the efficiency of cortical tracts. Another crucial mechanism, in particular at the early stage, is the regression of diaschisis effects. Diaschisis is the term used to describe the effect of brain injury to a certain area to inhibit connected, noninjured areas. In this specific case, recovery consists of the removal of this inhibition and return to normal function. Theoretically, synaptogenesis, as well as axonal and collateral sprouting, could also play a role after the first stages of recovery (Heiss, Kessler, Karbe, Fink, & Pawlik, 1993; Heiss et al., 1997; Karbe, Thiel, Weber-Luxenburger, Herholz, Kessler, & Heiss, 1998). However, these phenomena are very limited in space, and their contribution to clinical improvement in aphasics remains

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hypothetical. The notion of redundancy assumes that there is an excess of neurons and connections for a given function, so that neural tissue can be lost without functional consequences, because the uninjured neurons in the damaged area function as spare systems that can compensate for those that are nonfunctional. Finally, a functional cortical reorganization involving structures not primarily and directly involved in normal language functions might also take place. This vicariation phenomenon might occur even at an early stage of clinical improvement, probably by means of bringing into play silent synapses (either by release of previous inhibition or by increase of synaptic efficiency). How recovery may be achieved by the brain and how vicariation, redundancy, and diaschisis may take part in this process are hotly debated. Recovery may be achieved by adopting novel cognitive strategies for performance (that is, recruitment of uninjured cerebral areas, which are usually not necessary for the lost function in the intact brain). On the other hand, recovery may be achieved because of the involvement of homotopic (that is, homologous) areas of the contralateral hemisphere that may have compensatory function. Likewise, recovery may be due to the recruitment of perilesional areas surrounding the lesion, which gradually return to normal metabolic values and contribute over time to restore the impaired language function. Which mechanisms effectively participate in the language recovery processes, in which temporal succession they operate, and which of them is the most efficient are, so far, unanswered questions. In principle, vicariation, redundancy, and diaschisis may be involved in combination. For instance, adopting a novel cognitive strategy may be possible by a combination of left- (redundancy) and right-hemispheric (vicariation) recruitment. Modern neuroimaging techniques, in particular functional MRI (fMRI), allow us to test directly the role of these mechanisms. For instance, several studies have highlighted the presence of increased right-sided activation during the performance of language tasks in recovered aphasics. Weiller et al. (1995) reported a pioneering group study of six partially recovered patients with Wernicke’s aphasia. The patients’ cerebral perfusion was measured with positron emission tomography (PET) at rest and during nonword repetition and verb generation. According to a classical “subtractive” design, each language condition was compared with the rest in order to detect the areas of significant task-related activation. The same activation paradigm was applied to a group of normal controls, and the results provided the baseline to evaluate the presence of functional reorganization. The main conclusion was that, in comparison to control subjects, the patient group had a more extensive recruitment of frontal and temporal right-hemispheric regions, homotopical to the language areas of the left hemisphere. The interpretation that the increased right-hemispheric activation was responsible for aphasia recovery must be considered with caution. While the patients were largely recovered, as shown by the change in their aphasia test scores, the verb-generation task is very demanding and calls for

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an extensive activation of the right hemisphere, which was also observed in many normal right-handed subjects (Frackowiak, 1997). Furthermore, the use of a group analysis decreases the likelihood of detecting activation in perilesional areas, which will necessarily vary in individual subjects because of differences in lesion size and location. The results of Weiller et al. (1995) were considered to support the capacity of the right hemisphere to take over the damaged dominant hemisphere by means of its compensatory linguistic skills; at the same time, many other studies ascribe the contribution of preserved areas of the left hemisphere to a better and long-term recovery. In particular, follow-up studies with aphasic patients have revealed the existence of a temporal gradient in the enrollment of cerebral reorganization mechanisms after stroke. The initial employment of undamaged homologous areas of the right hemisphere is followed by their gradual discarding and concomitant, significant increasing of activity in lefthemispheric perilesional areas. The passage of functional competence from the right to the left is associated with improvement of linguistic performances (Karbe et al., 1998). Cao, Vikingstad, George, Johnson, and Welch (1999) reported an fMRI study conducted with aphasics in which there was a significant inverse correlation between activations of the nondominant and dominant hemisphere when subjects performed a picture-naming task and a verb-generation task. Indeed, a better and long-term recovery was associated with left-sided activations. Furthermore, Warburton, Price, Swinburn, and Wise (1999) have demonstrated in recovered aphasic patients, who underwent PET scans while performing a word-retrieval task, that even limited salvage of perilesional tissue may have an important impact on recovery. In line with this experimental evidence, some authors have argued that “righthemispheric recruitment” in functional recovery may simply reflect reliance on additional cognitive and linguistic resources, which are not required by normal subjects during linguistic processing. A similar interpretation was proposed by Rosen et al. (2000) to account for the increased perilesional activation in the area of the left inferior frontal gyrus in patients with superior recovery during a word-stem-completion task. Our recent study with fMRI has given similar results (Perani et al., 2003). Studies of recovered aphasic subjects indicate that the pattern of reorganization observed during word-fluency tasks is heterogeneous, but shows mainly left-hemispheric activation, in the same areas activated in normal subjects, or in other language-related regions. In the case of comprehension, it is also likely that compensatory activation in what appears to be a largely redundant cerebral network may be responsible for improvement. Zahn et al. (2004) studied a group of seven global aphasics who, 6–12 months post-onset, had partially recovered single-word comprehension. During a semantic judgment task, the patients showed activations in areas observed to be engaged in lexicalsemantic comprehension and which were also seen in normal subjects. The balance between ipsilateral and contralateral contributions is probably a crucial component of recovery. Recently, Fernandez et al. (2004) have

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performed a longitudinal study in a patient with conduction aphasia. At 1 month post-onset, during a phonological task, the patient showed an extensive engagement of right-hemispheric areas, homotopic to those activated by normal subjects. When the patient was reassessed 12 months post-onset, there was an enhanced activation of perilesional left hemispheric areas.

Pre- and post-speech therapy fMRI correlations Most of the above functional neuroimaging studies were “single-session” studies; better insight into this issue may be gained by the use of “repeated” functional neuroimaging studies that aim to monitor the recovery process and/or speech therapy in aphasics. This would definitely allow us to document the processes involved in language recovery. For example, Cardebat et al. (2003) reported bihemispheric increases in language-related perisylvian regions, and decreases in regions associated with emotional processing, in a group of aphasic patients studied twice with PET over a period of 6 months. However, the number of studies that attempted to evaluate the neural basis of training-induced modifications of language performance is still limited. One of these studies was conducted, using PET, by Belin et al. (1996). These authors studied patients with chronic nonfluent aphasia who had shown considerable improvement after the introduction of additional rehabilitation training with melodic intonation therapy (MIT). This treatment involves speaking with exaggerated prosody, characterized by a melodic component (Albert, Sparks, & Helm, 1973). Patients were poor at repeating words with a natural intonation, but improved when they used an MIT-like intonation. The pattern of brain activation in comparison with the rest state indicated extensive right-sided involvement during single word repetition with natural intonation. However, in the other active task, which required repetition of words with MIT, the right hemisphere was reported to be deactivated, and a significant increase was found in the left frontal areas. The authors argued that the right-sided activations might reflect a “maladaptive” functional reorganization, due to the presence of the left lesion itself, while actual recovery mediated by MIT training might be associated with the reactivation of left-hemispheric undamaged structures. This latter hypothesis is supported by evidence suggesting that in the case of right-sided activation, recovery is rarely complete and residual deficits usually persist (Cappa, 2000). An important role of the right hemisphere is, however, suggested by the study of Musso, Weiller, Kiebel, Muller, Bulau, and Rijntjes (1999), who investigated with PET the neural correlates of intensive verbal comprehension training in a group of aphasics. Intensive 2-h language comprehension training on a modified version of the Token Test (De Renzi & Vignolo, 1962) was carried out during the PET interscan intervals. The training entailed an increase of correct answers on the Token Test in all patients. Performance on this test was positively correlated with the pattern of rCBF (regional cerebral blood flow) in the right homologs of Wernicke’s and Broca’s areas. This study

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demonstrated that intensive verbal comprehension training recruited rightsided cerebral regions. However, it is difficult to draw strong conclusions from the study, because it is unclear how the results of a 2-h training may be extended to what happens normally during speech-therapy-induced language recovery. It is noteworthy that another “acute training” study reported rightsided effects. Blasi et al. (Blasi, Young, Tansy, Petersen, Snyder, & Corbetta, 2002) found that the learning of a stem-completion task was associated with specific response decrements in the right frontal and occipital cortex, rather than in the left-sided network engaged by normal subjects. More recently, Léger et al. (2002) compared the results of fMRI during a naming task, pre- and post-rehabilitation, in a patient with prominent phonological errors in speech production. The main difference between the two studies was a reactivation of perilesional left-hemispheric areas, in particular Broca’s region and the supramarginal gyrus in the post-treatment study. Another interesting effect after rehabilitation has been recently reported by Peck et al. (2004): the training resulted in a return of the time-to-peak of the BOLD response during word generation in selected brain regions, paralleling the improvement in the speed of word finding in three treated aphasic patients. While the differences observed after rehabilitation in these studies may reasonably be considered to reflect treatment effects, the evidence remains indirect, and is based on the fact that the neural effects are parallel to the behavioral improvements. An attempt to overcome these limits is a recent study performed in our laboratory (Vitali et al., 2007). Using event-related, functional MRI (er-fMRI), we monitored the neural correlates of naming performance in two anomic patients ( patients S.A. and G.R.), before and after specific language therapy for anomia (phonologically cued naming training). A set of pictures that the patients could not name either spontaneously or after being phonologically cued, was selected for intensive speech therapy. The latter consisted in repetitively cuing patients, starting with the initial syllable of the target word and subsequently adding lacking syllables, until the correct answer was produced. After acquisition of the first er-fMRI session, training was intensively administered on a daily basis by a speech pathologist, until a 50% correct naming performance (at least) on the training picture set was achieved (8 weeks for S.A. and 4 weeks for G.R.). Before and after specific speech therapy, an er-fMRI acquisition was performed, during which patients had to overtly name the visually presented pictures of the experimental set and items of a control set (that patients were able to name prior to admission to our study). Improvement in overall naming performance upon therapy administration was more pronounced in patient S.A. than in G.R. In both patients, naming was mainly associated with activations in the nondominant hemisphere before starting speech therapy, while perilesional areas of the dominant hemisphere were mainly activated after speech therapy (Figure 8.1). This finding suggests that the perilesional areas of the dominant hemisphere may be crucial for effective

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Figure 8.1 The pattern of brain activity is measured by functional magnetic resonance imaging, associated with anomia (left column, pre-speech therapy) and with successful naming performance (right column, post-speech therapy) in two anomic patients (S.A., top rows; G.R. bottom rows) (see text for further details). As may be observed, a hemispheric shift of brain activity associated with a better performance in naming occurred in both patients. However, in G.R., also the right homolog of Broca’s area was activated, probably because his original brain lesion extended into the left Broca’s area proper. Areas involved in phonological processing are circled (red circles = Broca’s area; green circles = supramarginal gyrus), emphasizing that both patients used the trained phonological strategies for successful naming (modified from Vitali et al., 2007). (This figure is published in color at www.psypress.com/brainscans-etc/)

recovery. However, in patient G.R., also the right homolog of Broca’s area proper was found to be activated, probably because his original brain lesion extended into the left Broca’s area (Figure 8.1). In the absence of the left Broca’s area, successful naming may be mediated by its right homolog area. These findings agree with studies that have highlighted the ability of the contralateral nondominant hemisphere (in particular of the perisylvian areas) to compensate for a loss of function in the damaged dominant hemisphere. It is also worth underlining that the anomia-specific rehabilitation, based on phonological cuing, was associated with activation in brain areas classically ascribed to phonological processing, phonological working memory, and lexical retrieval (left inferior frontal gyrus and supramarginal gyrus); this activation pattern could reflect a facilitated access and retrieval of lexical items from the mental lexicon by enhanced and trained sublexical, phonological strategies.

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Conclusion Functional neuroimaging techniques brought to the fore new evidence in the cortical organization of cognitive functions that previously were difficult to study due to the limited information classical methods may provide. These techniques are suitable for a clinical use; that is, to study the cortical reorganization of language areas after brain injury. The repeatability of fMRI over time allows one to investigate how patterns of cerebral activity may change during the course of recovery and to observe consequently the influence of treatment on brain functioning. Without these new techniques, it would have been quite impossible to document the cerebral plasticity that may occur during recovery of function. In particular, the results of the research conducted in our laboratory (Vitali et al., 2007) have shown that the activation of spared perilesional tissue in the left hemisphere is associated with a better and long-term language recovery. Moreover, the training-induced cerebral reorganization observed in both patients reflected also the ability of the damaged brain to display plastic changes in response to a specific rehabilitative treatment. Furthermore, it supports the usefulness of functional imaging as a tool to assess the neurobiological effects of specific rehabilitation training. Apart from increasing our knowledge of the mechanisms of functional recovery and their temporal sequence, pre- and postoperative language, fMRI is revolutionizing the field of neurolinguistics: instead of thinking in terms of the classical anatomoclinical correlations dating back to Broca’s time, we are now able to draw correlations directly between cerebral activity and linguistic performance. Thus, the actual question is no longer “What is injured?”, but “What is working?”

References Albert, M. L., Sparks, R. W., & Helm, N. A. (1973). Melodic intonation therapy for aphasia. Archives of Neurology, 29, 130–131. Alexander, M. P. (1989). Clinical-anatomical correlations of aphasia following predominantly subcortical lesions. In F. Boller and J. Grafman (Eds.), Handbook of neuropsychology (vol. 2). Amsterdam: Elsevier. Belin, P., Van Eeckhout, P., Zilbovicius, M., Remy, P., Francois, C., Guillaume, S., et al. (1996). Recovery from non-fluent aphasia after melodic intonation therapy: A PET study. Neurology, 47, 1504–1511. Blasi, V., Young, A. C., Tansy, A. P., Petersen, S. E., Snyder, A. Z., & Corbetta, M. (2002). Word retrieval learning modulates right frontal cortex in patients with left frontal damage. Neuron, 36, 159–170. Cao, Y., Vikingstad, E. M., George, K. P., Johnson, A. F., & Welch, K. M. (1999). Cortical language activation in stroke patients recovering from aphasia with functional MRI. Stroke, 30, 2331–2340. Cappa, S. F. (2000). Recovery from aphasia: Why and how? Brain and Language, 71, 39–41. Cardebat, D., Demonet, J. F., De Boissezon, X., Marie, N., Marié, R. M., Lambert, J.,

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et al. (2003). Behavioral and neurofunctional changes over time in healthy and aphasic subjects: A PET language activation study. Stroke, 34, 2900–2906. De Renzi E., & Vignolo, L. (1962). The Token Test: A sensitive test to detect receptive disturbances in aphasics. Brain, 85, 665–678. Fernandez, B., Cardebat, D., Demonet, J. F., Joseph, P. A., Mazaux, J. M., & Barat, M. (2004). Functional MRI follow-up study of language processes in healthy subjects and during recovery in a case of aphasia. Stroke, 35, 2171–2176. Frackowiak, R. S. J. (1997). The cerebral basis of functional recovery. In R. S. J. Frackowiak, K. J. Friston, C. Frith, R. J. Dolan, & J. C. Mazziotta (Eds.), Human brain function (pp. 275–299). New York: Academic Press. Furlan, M., Marchal, G., Viader, F., Derlon, J. M., & Baron, J. C. (1996). Spontaneous neurological recovery after stroke and the fate of the ischemic penumbra. Annals of Neurology, 40, 216–226. Heiss, W., Kessler, J., Karbe, H., Fink, G., & Pawlik, G. (1993). Cerebral glucose metabolism as a predictor of recovery from aphasia in ischemic stroke. Archives of Neurology, 50, 958–964. Heiss, W., Kessler, J., Thiel, A., Ghaemi, M., & Karbe, H. (1997). Speech-induced cerebral metabolic activation reflects recovery from aphasia. Journal of the Neurological Sciences, 145, 213–217. Karbe, H., Thiel, A., Weber-Luxenburger, G., Herholz, K., Kessler, J., & Heiss, W. D. (1998). Brain plasticity in post-stroke aphasia: What is the contribution of the right hemisphere? Brain and Language, 64, 215–230. Kertesz, A., Lesk, D., & McCabe, P. (1977). Isotope localization of infarcts in aphasia. Archives of Neurology, 34, 590–601. Léger, A. Demonet, J. F., Ruff, S., Aithamon, B., Touyeras, B., Puel, M., et al. (2002). Neural substrates of spoken language rehabilitation in an aphasic patient: An fMRI study. NeuroImage, 17, 174–183. Mahagne, M. H., Darcourt, J., Migneco, O., Fournier, J. P., Thiercelin, D., Ducœur S., et al. (2000). Early (99m)Tc-ethylcysteinate dimer brain SPECT patterns in the acute phase of stroke as predictors of neurological recovery. Cerebrovascular Disease, 10, 364–373. Mazzocchi, F., & Vignolo L. A. (1979). Computer assisted tomography in neuropsychological research: A simple procedure for lesion mapping. Cortex, 14, 13–144. Musso, M., Weiller, C., Kiebel, S., Muller, S. P., Bulau, P., & Rijntjes M. (1999). Training-induced brain plasticity in aphasia. Brain, 122, 1781–1790. Peck, K. K., Moore, A. B., Crosson, B. A., Gaiefsky, M., Gopinath, K. S., White, K., et al. (2004). Functional magnetic resonance imaging before and after aphasia therapy: Shifts in hemodynamic time to peak during an overt language task. Stroke, 35, 554–559. Pedersen, P. M., Jorgensen, H. S., Nakayama, H., Raaschou, H. O., & Olsen, T. S. (1995). Aphasia in acute stroke: Incidence, determinants, and recovery. Annals of Neurology, 38, 659–666. Perani, D., Cappa, S. F., Tettamanti, M., Rosa, M., Scifo, P., Miozzo, A., et al. (2003). An fMRI study of word retrieval in aphasia. Brain and Language, 85, 357–368. Rosen, H. J., Petersen, S. E., Linenweber, M. R., Snyder, A. Z., White, D. A., Chapman, L., et al. (2000). Neural correlates of recovery from aphasia after damage to left inferior frontal cortex. Neurology, 55, 1883–1894. Sarno, M. T., & Levita, E. (1971). Natural course of recovery in severe aphasia. Archives of Physical Medicine and Rehabilitation, 52, 175–179.

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Vignolo, L. A. (1964). Evolution of aphasia and language rehabilitation: A retrospective exploratory study. Cortex, 1, 344–367. Vitali, P., Abutalebi, J., Tettamanti, M., Danna, M., Ansaldo, A. I., Perani, D., et al. (2007). Training-induced brain-remapping in chronic aphasia: A pilot study. Neurorehabilitation and Neural Repair, 21, 152–160. Warburton, E., Price, C. J., Swinburn, K., & Wise, R. J. (1999). Mechanisms of recovery from aphasia: Evidence from positron emission tomography studies. Journal of Neurology, Neurosurgery, and Psychiatry, 66, 155–161. Weiller, C., Isensee, C., Rijntjes, M., Huber, W., Müller, S., Bier, D., et al. (1995). Recovery from Wernicke’s aphasia: A positron emission tomographic study. Annals of Neurology, 37, 723–732. Zahn, R., Drews, E., Specht, K., Kemeny, S., Reith, W., Willmes, K., et al. (2004). Recovery of semantic word processing in global aphasia: A functional MRI study. Brain Research and Cognitive Brain Research, 18, 322–336.

9

Aphasia rehabilitation Anna Basso

In this chapter, I shall consider an important problem faced by aphasia therapy efficacy studies, an issue that we—in collaboration with Professor Luigi Vignolo—started to study some 40 years ago at the neurological clinic of Milan University, where a few years earlier an aphasia rehabilitation centre had been opened. Many different techniques and experimental designs have been employed in an effort to solve the thorny problem of aphasia therapy efficacy, but no general agreement has been reached, notwithstanding the increasing body of evidence that aphasia therapy works. Some researchers still maintain that the reported studies are not experimentally sound and that their results cannot be taken as evidence; they say that such studies should be based on randomized, controlled trials (RCTs). I am not going to discuss whether or not RCTs provide the best scientific method for the assessment of aphasia treatment efficacy, but I shall focus on a different problem: the need to define the disorder to be treated and the treatment to be evaluated before evaluating its efficacy. This chapter starts with a brief review of aphasia therapy efficacy studies and the definition of the terms efficacy and effectiveness. Subsequently, examples of different production disorders and different treatments are given, followed by a discussion of the importance of the amount of treatment in evaluating its efficacy. The conclusion will be drawn that the question of aphasia therapy efficacy is too broad and that the aphasic disorder to be treated, the chosen treatment, and its implementation must be defined first.

Summary of research on aphasia therapy efficacy The first group studies on treatment efficacy were performed in the 1950s and 1960s. Only rehabilitated subjects were included, and their results at a first and a second (generally subjective) evaluation were compared. All authors (Butfield & Zangwill, 1946; Leischner & Lynk, 1967; Marks, Taylor, & Rusk, 1957; Sands, Sarno, & Shankweiler, 1969; Sarno & Levita, 1979) agreed that aphasia therapy is effective, but they ignored the possible effect of spontaneous recovery. This shortcoming was corrected in the following group of studies that compared treated and untreated subjects, evaluated by

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standardized batteries. The results of these group studies were equivocal because therapy was found to have a significant effect on recovery in some (Basso, Capitani, & Vignolo, 1979; Basso, Faglioni, & Vignolo, 1975; Gloning, Trappl, Heiss, & Quatember, 1976; Hagen, 1973; Poeck, Huber, & Willmes, 1989; Shewan & Kertesz, 1984), but not in all studies (Lincoln, McGuirk, Mulley, Lendrem, Jones, & Mitchell, 1984; Pickersgill & Lincoln, 1983; Vignolo, 1964). Other criticisms of this group of studies refer to the heterogeneity of the subjects (different age, aetiology, education, etc.) and the nonrandom allocation of subjects to the treated and untreated group. Exceptions to the non-random allocation of subjects are the US Veterans Administration studies (Marshall et al., 1989; Wertz et al., 1981, 1986) and Lincoln et al.’s study (1984). Treated and untreated subjects were also compared in a wellcontrolled study, in which the effect of therapy was studied in pairs of subjects—one rehabilitated and one non-rehabilitated—matched for type and severity of aphasia, lesion site, age, and educational level (Mazzoni, Vista, Geri, Avila, Bianchi, & Moretti, 1995). Treated subjects recovered more than untreated subjects. Another way of dealing with the problem of spontaneous recovery is to study chronic aphasic subjects beyond the period of spontaneous recovery. This has been done in a number of studies (Aten, Caligiuri, & Holland, 1982; Broida, 1977; Mackenzie, 1991; Wepman, 1951), which all found a certain amount of recovery, always ascribed to therapy, since all subjects were supposed to have reached a plateau before entering the study. The effect of rehabilitation has also been studied by comparing results obtained by speech therapists and by volunteers (David, Enderby, & Bainton, 1982; Hartman & Landau, 1987; Marshall et al., 1989; Meikle et al., 1979; Wertz et al., 1986). This approach permits circumvention of the ethical problem of denying rehabilitation to a group of patients and, at the same time, it responds to the criticism that rehabilitated and non-rehabilitated subjects differ in the amount of attention they receive. None of the studies that adopted this strategy found significantly better results for the group of subjects treated by speech therapists. Taken separately, none of the aforesaid studies provide sufficient unequivocal evidence to demonstrate that aphasia therapy is effective. It should be noted that negative results cannot demonstrate that aphasia therapy is not effective. The null hypothesis cannot be proved; it can only be disproved. However, more studies support the efficacy of aphasia therapy. It can be objected that more “positive” than “negative” papers have been published because negative findings tend not to be published, the so-called file-drawer problem. While it is not possible to reach certainty, Robey (1998) studied this problem by plotting sample size over effect size and concluded that there is no publication bias. More recently, scientific evidence in support of the efficacy of aphasia therapy has come from meta-analyses. A meta-analysis is a scientific way to synthesize research findings and to establish the weight of the scientific evidence bearing on a certain research hypothesis. Three meta-analyses have

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supported the efficacy of aphasia therapy (Robey, 1994, 1998; Whurr, Lorch, & Nye, 1992). Greener, Enderby, and Whurr (1999) conducted a review analysis for the Cochrane Collaboration. The inclusion criteria were strict: all subjects had to have a vascular lesion and to be randomly allocated to the treated and untreated group. Only two studies comparing treated and untreated subjects were found, and the authors concluded: “Speech and language therapy treatment for people with aphasia after a stroke has not been shown either to be clearly effective or clearly ineffective within a RCT” ( p. 1).

Level of evidence scales Means for evaluating the results obtained in outcome research are called level of evidence scales. Two large reviews on level of evidence for cognitive rehabilitation were performed (Cappa, Benke, Clarke, Rossi, Stemmer, & van Heugten, 2003; Cicerone et al., 2000). Cicerone et al. (2000) classified class I studies as prospective RCTs, class II studies as prospective cohort studies, retrospective case-control studies, and clinical series with well-designed controls; and, finally, class III studies as clinical series without controls. Cappa et al. (2003) classified evidence level (EL) as Ia when based on meta-analysis of RCTs, as Ib when based on at least one RCT, as IIa when based on welldesigned, controlled studies, and as IIb when based on well-designed, quasiexperimental studies. Thus, both groups of researchers consider the statistical design of the study of primary importance, and the RCTs as the reference standard. No one would challenge the view that a well-controlled study provides more adequate information than a methodologically inadequate study, but it is striking that the amount of provided therapy has never been considered as an exclusion or inclusion criterion. The effect of the amount of therapy has been studied and found to affect recovery significantly. However, the evidence of two hypothetical studies, a positive and a negative one, carried out with the same statistical work-up, would be considered equal, independently of the amount of therapy. This is questionable, since the amount of therapy (hypothetically smaller in the negative study and larger in the positive one) could by itself explain the different results.

Efficacy and effectiveness It is possible to explain, at least partially, the non-complementary conclusions from different studies if one takes into consideration the difference between efficacy and effectiveness as postulated by the Office of Technology Assessment (OTA, 1978). Efficacy is defined as “the probability of benefit to individuals in a defined population from a medical technology applied to a given medical problem under ideal conditions of use” ( p. 16); effectiveness has been defined in the same terms except for the conditions of use, which are average.

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Therefore, it seems logical that the efficacy of a treatment should be proven first. Only after a treatment has been demonstrated to be efficacious, can effectiveness be investigated by changing, for example, the duration of the treatment to find out what is the shortest efficacious duration. Incidentally, two of the most frequently cited “negative” studies (David et al., 1982; Lincoln et al., 1984) are effectiveness, and not efficacy, studies, as clearly acknowledged by the authors themselves. David et al. (1982), for instance, wrote, “We attempted to design a study which represented the kind of patients with aphasia and the amount of treatment normally encountered in speech therapy departments in this country” (p. 959), and David (1983) adds: It is likely that more intensive treatment would produce more positive changes over a longer period in most patients. Unfortunately the British speech therapy service is not usually able to provide many patients with more intensive treatment than was investigated in our study. (David, 1983, p. 691) The only conclusion that can be drawn is not that aphasia treatment is not efficacious, but that the amount of treatment provided in the way it was provided was not effective.

Variability of the disorder As stated above, I leave the question open whether or not aphasia therapy efficacy has been demonstrated and what the best experimental design is to study it. I am more interested in tackling a different and, in my view, logically preceding issue. To study the efficacy of a given medical treatment, we must know which problem we want to treat and which treatment is used to treat it. In aphasia therapy efficacy studies, neither the problem—aphasia—nor the treatment has been clearly defined. When the first efficacy studies were conducted, our knowledge of aphasia was scantier than today. No one would have questioned that people with aphasia differ not only because of the severity of the disorder but also because there are different forms of aphasia, such as Broca’s, Wernicke’s, and conduction aphasia. Researchers observed contrasting patterns of performance for different patient groups and argued that distinct collections of symptoms (that is, syndromes) occur as a result of brain lesions to different neural substrates. It was then believed that the underlying disturbance for each syndrome could ultimately be linked to a specific brain area. Over the past two to three decades, patients’ data have increasingly been used to constrain claims about the structure of the normal cognitive system. The emphasis was not on the relationship between a constellation of symptoms and a brain area but on the relationship between cognitively impaired performance and the normal cognitive system. Cognitive neuropsychologists did not engage in the investigation of syndromes. They mostly engaged in thorough investigations

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of the impaired performance of single patients, since careful analysis of the impaired performance of a single patient can provide a basis for fine-grained hypotheses about the structure of normal cognitive mechanisms. This increased interest in the underlying damage has obvious consequences for therapy. If we can identify different functional damages, we should also be able to instantiate different treatments. To illustrate the variability of the aphasic disorders, I report samples of the spontaneous speech of four aphasic subjects, the first with verbal jargon, the second with phonemic jargon, the third with anomia, and the last with agrammatic speech. All subjects described the same picture of a living room in which a woman is knitting, a man sits in an armchair reading a newspaper, a young girl is watching television, a boy is playing with cubes, and a cat is playing with a ball of wool. Verbal jargon Subject P.M., a 62-year-old man with 17 years of formal education, had suffered a cerebrovascular accident 2 months before assessment at the aphasia unit of Milan University. A CT scan showed a temporal-parietal lesion in the left hemisphere. His speech was fluent with frequent paraphasias; he scored 6 on the Token Test (De Renzi & Faglioni, 1978) and 21 on Raven’s Coloured Progressive Matrices (RCPM) (Raven, 1965). He described the picture in the following way: “What do we see here? And the girl the boys the share because has difficulties here where the children lean who tie the girls here who carry the (feminine singular) plugs those for the usual lamps who however do not look. Now then, we were saying that the children through it looked at the light and the children made the reading for the plug light. The girls moved the sight of the yo yo youngs who are passing here the visit of the children with the whole plug of the children the sight of the children and the fastening.” [Cosa vediamo qua? E la ragazza i ragazzi la quota perché ha difficoltà qui dove poggiano i bambini che legano le bambine qua che portano la prese quelle per le lampade solite che però non guardano. Allora si parlava che i bambini attraverso si guardava la luce e i bambini facevano la lettura per la presa della luce. Le bimbe hanno mosso la vista delle gio gio giovani che passano qui la vista dei bambini con tutta la presa dei bambini la vista dei bambini e la chiusura.] Phonemic jargon G.R., a 49-year-old man with a degree in architecture, underwent total ablation of a left temporal tumour a month before testing. A CT scan performed after surgery showed an ischaemic lesion in the left temporal-parietal-occipital region. G.R. had fluent speech, characterized by phonemic jargon. He scored 4 on the Token Test and 11 on the RCPM.

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His description is reported here; the translation of the rare sequences that corresponded to existing Italian words is written in parentheses. “Normerugia dorcuore sircora sircore mori chiari (light) brava bravo (good; feminine, masculine) qui (here) nustase dormire (sleep) oce seluta chestari chelone sostali iusta questo (this) cocchieri no no nola questi e basta basta (these and enough enough).” Anomia A.S., a 62-year-old woman with a degree in biology, was admitted to hospital following an intracerebral left temporal haemorrhage; neurosurgery was not performed, and 3 months later a CT scan revealed a hypodense area in the left subcortical temporal region. She was tested 2 months later at the aphasia unit. Her speech was fluent and abundant with frequent word-finding difficulties. She scored 18 on the Token Test and 20 on the RCPM. Her description of the picture was as follows: “The dog that plays with . . . I don’t know what’s its name . . . of the owner who is knitting. Here there is the television but it is disconnected the . . . what do you say . . . the back, well! The girl who looks and the father who is looking the . . . the small brother is playing with 5 cards and the shorter cards and one in hand. Here there is . . . I don’t remember its name, and there are . . . one two bookcases.” [Il cane che gioca con . . . non so come si chiama . . . della padrona che sta lavorando a maglie. Qui c’è la televisione però è staccato il . . . come si dice . . . il didietro, insomma . . . la bambina che guarda e il papà che sta guardando il . . . un fratellino sta giocando con 5 carte più le carte più corte e una in mano. Qui c’è . . . non mi ricordo come si chiama e ci sono . . . una, due librerie.] Agrammatism U.S., a 43-year-old woman with 13 years of formal education, taught mathematics. Four months before testing, she suffered a rupture of an aneurysm of the left middle cerebral artery, which was immediately clipped. Her speech was nonfluent, halting, and effortful and presented the characteristic of agrammatism. She scored 22 on the Token Test and 34 on the RCPM. She described the picture as follows: “Grandfather to read newspaper girl television, cinema . . . boy lego . . . not the grandfather, husband. Stiches, stich, cat, ball, wool.” [Nonno leggere giornale, bambina TV, cine . . . bambino lego . . . non il nonno, marito! Maglie, maglia, gatto, palla, lana.] It is difficult to believe that underlying these contrasting speech outputs is the same functional damage; that is, that they are the result of one and the same disorder. At a very superficial level of analysis, we can hypothesize that agrammatic speech has to do with sentence construction processing, anomic production with the processing of the phonological forms of words, semantic

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jargon with the relationship between a word form and its meaning, and phonemic jargon with phonological planning. If this is the case, that is, if these speech samples must be attributed to different underlying deficits, they require different treatments, even if they can all be grouped under the generic definition of production disorders.

Variability of the treatment content Under the vague definition of aphasia therapy, we can find treatments that differ widely in their content and in the rationale they are based on. What really happens during treatment is largely unknown, and we use the words treatment or therapy to indicate any exchange between an aphasic subject and a person who is professionally entitled to treat the patient. I briefly report two treatments, the first for global aphasia and the second for transcortical motor aphasia, which have been considered interesting enough to be published but which, in my opinion, well illustrate how poorly motivated treatments can be. Collins (1983) argues that the first aim in a global aphasic subject’s treatment is the intentional production of “yes” and “no”. He proposes that the therapist physically assist the subject with five repetitions of yes (head nod) while he or she says “yes” and with five repetitions of no (side-to-side head movements) while saying “no”. The second step consists of alternatively saying “yes” and “no” while physically assisting the subject to nod and move the head from left to right. Finally, the therapist asks a simple question and physically helps the subject to move the head in the appropriate way while saying either “yes” or “no”. Assuming that there are motor processing problems in transcortical motor aphasia, Johnson (1983) considers improvement of motor processing the primary goal in the treatment of transcortical motor aphasia. The subject is first required to imitate gross conventional movements, such as waving goodbye, and then to pantomime an action, such as throwing a ball. The final step consists in having the subject perform the same action (throwing a ball) while saying, “I am throwing a ball.” These are two extreme examples, and I hope that nobody today would agree with these suggestions, but the literature is still full of examples of different treatments for the same impairment and similar treatments for different impairments, and it is highly unlikely that they all work adequately. As an example, some proposals for the treatment of agrammatism will be discussed. Agrammatism has always attracted the attention of researchers and therapists. Many theories have been proposed to explain this language disorder and many different interventions have been developed to treat it. Two intervention strategies derived from different theoretical interpretations of the disorder will be briefly illustrated. The treatment proposed by HelmEstabrooks, the Helm Elicited Language Program for Syntax Stimulation (HELPSS) (Helm-Estabrooks, Fitzpatrick, & Barresi, 1981; Helm-Estabrooks & Ramsberger, 1986), is derived from principles of behavioural psychology: if

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a response is associated with a given stimulus and the stimulus is presented many times, the response will be learned. HELPSS is based on a study by Gleason, Goodglass, Green, Ackerman, and Hyde (1975), in which a storycompletion technique was used to elicit spoken responses to 14 syntactic constructions with an order of difficulty from eight subjects with agrammatism. HELPSS incorporates the order of difficulty and the story-completion technique. Subjects are shown a picture, and the therapist describes it. For example, “Rob’s grandchild is bored. Rob gets a book, and he reads his grandchild a story. What does he do?” Target response: “He reads his grandchild a story.” Many instances of the same grammatical structure are presented, and when the subject is 90% correct, the therapist proceeds to the second level in which the target sentence is not spoken by the therapist. Jones (1986) proposed a therapeutic programme designed for a non-fluent aphasic subject with agrammatism. The programme is based on the hypothesis that the subject’s fundamental problem is in mapping meaning relations between semantics and syntax, that is, in the argument structure of verbs. Verbs form the basis of sentence construction and have a structure inherent to their meaning. The verb “eat”, for example, requires an animate actor who performs the action of eating—the agent—and something to be eaten—the food. Jones did not ask her agrammatic subject to produce sentences, as in the HELPSS method. The subject was required not to produce sentences but to analyse them. In a simple subject–verb–object sentence, the subject had to identify the verb and underline it. The role of the agent was then explained and the subject was required to find out who was the doer of the action in the sentence. The following step consisted in explaining to the subject that in many cases the action is performed on something and to ask him to isolate the undergoer (or patient) of the action in the sentence. These two interventions strategies are quite different; it cannot be excluded that they are equally efficacious for exactly the same subjects, but this seems rather implausible and published data do not permit comparison of their efficacy. In any case, it does not seem sensible to pool studies using different treatment methods and evaluate their efficacy simultaneously in all subjects.

Variability of treatment implementation Treatments do not vary only in their content; they also differ in the amount of therapy delivered and in its intensity. The issue of amount of therapy has been frequently addressed in aphasia research. A careful review of the studies that compared treated and untreated subjects shows that treatment was of short duration in all “negative” studies where it was not found to be effective (Levita, 1978; Lincoln et al., 1984; Pickersgill & Lincoln, 1983; Prins, Schoonen, & Vermeulen, 1989; Sarno, Silverman, & Sands, 1970; Vignolo, 1964), whereas it lasted for longer periods of time in all “positive” studies (Basso et al., 1975, 1979; Gloning et al., 1976; Hagen, 1973; Mazzoni et al., 1995). The difference between the mean number of therapy sessions in the

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positive and the negative studies was found to be significant (Bhogal, Teasell, & Speechley, 2003). The effect of amount of treatment was also studied by Robey (1998), who performed a meta-analysis of clinical outcomes for treatments of acquired aphasia. He calculated the effect size (an index of the observed departure from the null hypothesis) for 12 studies that reported data on amount of recovery. Results indicate that amount of recovery was positively correlated with length of treatment and number of sessions. A priori, we would expect inadequate treatment to have no effect. The available evidence suggests that aphasia therapy needs to be prolonged if it is to have any effect. However, studies of efficacy of aphasia therapy have been criticized for many reasons (the most frequent being that subjects were not randomly allocated to the treated and untreated group), but the question of the minimum amount of therapy required has never been raised.

Conclusion Researchers have done their best to tackle the question of the efficacy of aphasia therapy, and they have used different techniques (treated and untreated subjects, chronic aphasic subjects, and matched subjects). In the behavioural sciences, however, it is practically impossible to carry out an ideal experiment, and none of the reported studies stand above criticism. More or less welldesigned group studies have attempted to respond to the question of efficacy of aphasia therapy in the past when we did not appreciate as well as we do now how much even apparently similar aphasic symptoms can be the expression of widely different underlying damage. Consequently, aphasia therapy was less tailored to each subject than it is now. Some meta-analyses, which are attempts to put together the results of efficacy studies, were also performed. Metaanalyses are based on a literature search of studies concerned with efficacy, and studies considered inadequate are excluded from the meta-analysis. The metaanalyses performed on aphasia clinical outcomes were based on different data sets. Greener et al. (1999) used the most stringent criteria (100% of vascular subjects, randomly allocated to the treated and untreated group) and could only include two studies (Lincoln et al., 1984; Wertz et al., 1986). They could reach no conclusion about aphasia therapy efficacy. The results of the other meta-analyses confirm the efficacy of aphasia therapy. The bulk of experimental evidence is greatly in favour of the efficacy of aphasia therapy. However, I tried to show that the question, “Is aphasia therapy efficacious?”, is definitely too broad because there is no such thing as “aphasia” or “treatment for aphasia”. Aphasia and therapy for aphasia are comprehensive terms; under the cover term “aphasia”, many different disorders are grouped and various, totally independent treatments have been described for aphasic disorders. If we agree that aphasic disorders and their treatments are numerous, different, and independent, we must admit that a positive answer to the generic question, “Is aphasia therapy effective?”, would be of no help for people

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involved in aphasia therapy. A positive answer does not specify which treatment is effective for which disorder. A positive and uncontroversial response to such a question would have “political” importance because it could be used to obtain social investments in aphasia therapy, but it could in no way guide therapy. To solve the problem of the efficacy of aphasia therapy in a more scientifically correct way, researchers should agree on a small number of relatively homogeneous areas of disorders, such as single word processing, reading, and writing. Each of these areas is sufficiently large to justify research on its own; it covers various functional disorders that, however, are sufficiently homogeneous to be considered together. Furthermore, the minimum requirements to define what can be considered a treatment should be established. Unfortunately, at this moment, we are not in the position to agree on which treatments are sensible and merit evaluation and which are not. However, the content of a treatment should be clearly defined and reproducible, and the reasons why it is supposed to work should be clearly stated. Only if these minimal requirements are satisfied will it be possible to evaluate first the efficacy of a specific treatment for a given disorder and then its effectiveness in less ideal conditions. What we will probably find is that certain treatments for certain disorders work and others do not.

References Aten, J., Caligiuri, M. P., & Holland, A. L. (1982). The efficacy of functional communication therapy for chronic aphasic patients. Journal of Speech and Hearing Disorders, 47, 93–96. Basso, A., Capitani, E., & Vignolo, L. A. (1979). Influence of rehabilitation of language skills in aphasic patients: A controlled study. Archives of Neurology, 36, 190–196. Basso, A., Faglioni, P., & Vignolo, L. A. (1975). Étude controlée de la rééducation du langage dans l’aphasie: Comparaison entre aphasiques traités et non-traités. Revue Neurologique, 131, 607–614. Bhogal, S. K., Teasell, R., & Speechley, M. (2003). Intensity of aphasia therapy: Impact on recovery. Stroke, 34, 987–993. Broida, H. (1977). Language therapy effects in long term aphasia. Archives of Physical Medicine and Rehabilitation, 58, 248–253. Butfield, E., & Zangwill, O. L. (1946). Re-education in aphasia: A review of 70 cases. Journal of Neurology, Neurosurgery, and Psychiatry, 9, 75–79. Cappa, S., Benke, T., Clarke, S., Rossi, B., Stemmer, B., & van Heugten, C. M. (2003). EFNS guidelines on cognitive rehabilitation: Report on an EFNS Task Force. European Journal of Neurology, 10, 11–23. Cicerone, K. D., Dahlberg, C. Kalmar, K., Langenbahn, D. M., Malec, J. F., Bergquist, T. F., et al. (2000). Evidence-based cognitive rehabilitation: Recommendations for clinical practice. Archives of Clinical Medicine and Rehabilitation, 81, 1596–1615. Collins, M. (1983). Treatment of global aphasia. In W.H. Perkins (Ed.), Language handicaps in adults (pp. 25–33). New York: Thieme Stratton. David, R. M. (1983). Treatment of acquired aphasia: Speech therapists and volunteers compared. A reply. Journal of Neurology, Neurosurgery, and Psychiatry, 46, 690–691.

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David, R. M., Enderby, P., & Bainton, D. (1982). Treatment of acquired aphasia: Speech therapists and volunteers compared. Journal of Neurology, Neurosurgery and Psychiatry, 45, 957–961. De Renzi, E., & Faglioni, P. (1978). Normative data and screening power of a shortened version of the Token Test. Cortex, 14, 41–49. Gleason, J. B., Goodglass, H., Green, E., Ackerman, N., & Hyde, M. (1975). The retrieval of syntax in Broca’s aphasia. Brain and Language, 24, 451–457. Gloning, K., Trappl, R., Heiss, W. D., & Quatember, R. (1976). Prognosis and speech therapy in aphasia. In Y. Lebrun and R. Hoops (Eds.), Recovery in aphasics (pp. 57–62). Atlantic Highlands, NJ: Humanities Press. Greener, J., Enderby, P., & Whurr, R. (1999). Speech and language therapy for aphasia following stroke (Cochrane Review). In The Cochrane Library, Issue 4. Oxford: Update software. Hagen, C. (1973). Communication abilities in hemiplegia: Effect of speech therapy. Archives of Physical Medicine and Rehabilitation, 54, 454–463. Hartman, J., & Landau, W. M. (1987). Comparison of formal language therapy with supportive counselling for aphasia due to acute vascular accident. Archives of Neurology, 24, 646–649. Helm-Estabrooks, N., Fitzpatrick, P., & Barresi, B. (1981). Response of an agrammatic patient to a syntax program for aphasia. Journal of Speech and Hearing Disorders, 46, 422–427. Helm-Estabrooks, N., & Ramsberger, G. (1986). Treatment of agrammatism in long-term Broca’s aphasia. British Journal of Disorders of Communication, 21, 39–45. Johnson, M. G. (1983). Treatment of transcortical motor aphasia. In W. H. Perkins (Ed.), Language handicaps in adults (pp. 87–95). New York: Thieme Stratton. Jones, E. (1986). Building the foundations for sentence production in a non-fluent aphasia. British Journal of Disorders of Communication, 21, 63–82. Leischner, A., & Lynk, H. A. (1967). Neure Erfahrungen mit der Behandlung von Aphasien. Nervenartz, 38, 199–205. Levita, E. (1978). Effects of speech therapy on aphasics’ responses to the Functional Communication Profile. Perceptual and Motor Skills, 47, 151–154. Lincoln, N. B., McGuirk, E., Mulley, G. P., Lendrem, W., Jones, A. C., & Mitchell, J. R. A. (1984). Effectiveness of speech therapy for aphasic stroke patients: A randomized controlled trial. Lancet, 1, 1197–1200. Mackenzie, C. (1991). An aphasia group intensive efficacy study. British Journal of Disorders of Communication, 26, 275–29. Marks, M., Taylor, M., & Rusk, H. A. (1957). Rehabilitation of the aphasic patient: A summary of three years’ experience in a rehabilitation setting. Archives of Physical Medicine and Rehabilitation, 38, 219–226. Marshall, R. C., Wertz, R. T., Weiss, D. G., Aten, J. L., Brookshire, R. H., GarciaBunuel, L., et al. (1989). Home treatment for aphasic patients by trained nonprofessionals. Journal of Speech and Hearing Disorders, 54, 462–470. Mazzoni, M., Vista, M., Geri, E., Avila, L., Bianchi, F., & Moretti, P. (1995). Comparison of language recovery in rehabilitated and matched, non-rehabilitated aphasic patients. Aphasiology, 9, 553–563. Meikle, M., Wechsler, E., Tupper, A., Benenson, M., Butler, J., Mulhall, D., et al. (1979). Comparative trial of volunteer and professional treatments of dysphasia after stroke. British Medical Journal, 2, 87–89.

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OTA (Office of Technology Assessment) (1978). Assessing the efficacy and safety of medical technologies, (OTA-H-75). Washington, DC: US Government Printing Office. Pickersgill, M. J., & Lincoln, N. B. (1983). Prognostic indicators and the pattern of recovery of communication in aphasic stroke patients. Journal of Neurology, Neurosurgery, and Psychiatry, 46, 130–139. Poeck, K., Huber, W., & Willmes, K. (1989). Outcome of intensive language treatment in aphasia. Journal of Speech and Hearing Disorders, 54, 471–479. Prins, R. S., Schoonen, R., & Vermeulen, J. (1989). Efficacy of two different types of speech therapy for aphasic stroke patients. Applied Psycholinguistics, 10, 85–123. Raven, J. C. (1965). Guide to using the coloured progressive matrices sets A, Ab, B. London: H. K. Lewis. Robey, R. R. (1994). The efficacy of treatment for aphasic persons: A meta-analysis. Brain and Language, 47, 582–608. Robey, R. R. (1998). A meta-analysis of clinical outcomes in the treatment of aphasia. Journal of Speech, Language, and Hearing Research, 41, 172–187. Sands, E., Sarno, M. T., & Shankweiler, D. (1969). Long-term assessment of language function in aphasia due to stroke. Archives of Physical Medicine and Rehabilitation, 50, 202–206. Sarno, M. T., & Levita, E. (1979). Recovery in treated aphasia in the first year poststroke. Stroke, 10, 663–669. Sarno, M. T., Silverman, M., & Sands, E. (1970). Speech therapy and language recovery in severe aphasia. Journal of Speech and Hearing Research, 13, 607–623. Shewan, C. M., & Kertesz, A. (1984). Effects of speech and language treatment in recovery from aphasia. Brain and Language, 23, 272–299. Vignolo, L. A. (1964). Evolution of aphasia and language rehabilitation: A retrospective exploratory study. Cortex, 1, 344–367. Wepman, J. M. (1951). Recovery from aphasia. New York: Ronald Press. Wertz, R. T., Collins M. J., Weiss, D., Kurtzke, J. F., Friden, T., Brookshire, R. H., et al. (1981). Veterans Administration cooperative study on aphasia: A comparison of individual and group treatment. Journal of Speech and Hearing Disorders, 24, 580–594. Wertz, R. T., Weiss, D. G., Aten, J. L., Brookshire, R. H., Garcia-Bunuel, L., Holland, A. L., et al. (1986). Comparison of clinic, home, and deferred language treatment for aphasia. A Veterans Administration cooperative study. Archives of Neurology, 43, 653–658. Whurr, R., Lorch, M. P., & Nye, C. (1992). A meta-analysis of studies carried out between 1946 and 1988 concerned with the efficacy of speech and language therapy treatment for aphasic patients. European Journal of Disorders of Communication, 27, 1–17.

SECTION III

Skilled movement, music, and number-processing disorders

10 The forelimb apraxias Kenneth M. Heilman, Leslie J. Gonzalez Rothi, and Brenda Hanna-Pladdy

The purpose of this chapter is to describe the clinical aspects of five types of limb apraxia (limb-kinetic, ideomotor, ideational, dissociation, and conceptual) that represent disorders of skilled movement induced by deterioration of stored information in the “how” motor programming system.

Definition of apraxia Only organisms that move have brains, and thus one of the most important features of a brain is the control of movements that allow the organism to interact with and change the environment. The corticospinal system (which in man starts in layer 5 of Brodmann’s area 4 and travels through the internal capsule, cerebral peduncle, brainstem pyramids, and the dorsolateral spinal cord) activates specific motor units (e.g. anterior horn cells, motor roots, and nerves together with muscles) that can mediate an almost infinite number of difficult movements. Therefore, for successful interaction with the environment, the corticospinal neurons in the cerebral cortex must be guided by instructions or what can be termed the “how” programs. These programs instruct the motor system about (1) how to position one’s hand, forearm, and arm; (2) how to move the forelimb through space; (3) how to orient the limb toward the target of the limb’s action; (4) how to time movement and control speed; (5) how much force to exert; (6) how to order components of an act; and (7) how to solve mechanical problems. Disorders in the implementation of these “how” programs are termed apraxia, and each of the forms of apraxia we discuss in this chapter (limb-kinetic, ideomotor, ideational, dissociation, and conceptual) is a deficit in one or more of these “how” programs. According to Geschwind (1965), apraxia is clinically defined in part by what it is not. Hence, if a person fails to carry out a purposeful movement because of paralysis, abnormal movements (such as tremor, chorea, ballismus, or myoclonus), severe sensory-perceptual deficits, or cognitive impairment, this failure should not be attributed to apraxia. By this definition, when clinicians observe a disorder of purposeful movements that cannot be explained by these motor, sensory, or intellectual deficits, the patient is labeled as having apraxia. There are many forms of apraxia that involve

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various parts of the body; some of these include gait apraxia, speech apraxia, oculomotor apraxia, and even apraxia of the eyelids. We will not discuss all these forms of apraxia because this chapter will focus on forelimb apraxia. With regard to the forelimbs, patients without sensorimotor or severe intellectual deficits might have trouble dressing (dressing apraxia) or impairment in portraying the graphic representations of spatial relationships (constructional apraxia). Both of these disorders can be induced by attention-intention disorders, such as neglect, as well as visuospatial cognitive disorders. Thus, these two disorders might not be examples of deficits in the “how-praxis” systems and therefore will not be discussed in this chapter. The forms of limb apraxia that we will discuss in this chapter can be induced by a variety of diseases, including those that cause focal injuries such as cerebral infarction or those that are more widely distributed, including degenerative diseases such as Alzheimer’s disease or corticobasal degeneration. In this chapter we will also not discuss the specific diseases that can induce apraxia.

Brief history The term “apraxia” was originally proposed by Steinthal (1871); however, this word is derived from Greek and literally means without action. The absence of action is nowadays called akinesia, but the term “apraxia” has persisted. The greatest advance in the description and understanding of these disorders is contained in a series of papers written between 1900 and 1920 by Hugo Liepmann. He was a student of Carl Wernicke in Breskau, and Wernicke’s concepts of modularity and information-processing models had a great influence on Liepmann’s research. Unfortunately, Liepmann was never offered nor did he ever hold an academic appointment, although he was an excellent teacher and perhaps could have enhanced his creative endeavors. According to Kurt Goldstein (1970), he was told that if he changed his name and converted to Protestantism, he could obtain an academic appointment. However, he preferred to keep his name and to remain Jewish. He continued to practice in Germany until he developed severe Parkinson’s disease. Eventually, this disorder disabled him to such a degree that he took his own life. Liepmann (1920) described three forms of apraxia: limb-kinetic or melokinetic (similar to what Kleist subsequently called innervatory apraxia (1907)), ideomotor, and ideational. These three forms of limb apraxia will be discussed in the following sections, as well as two other forms of limb apraxia, dissociation and conceptual. Liepmann’s seminal papers brought about a “paradigmatic shift” in the understanding of motor control. From that time, little further important research was performed in this domain until Norman Geschwind and Edith Kaplan noted a patient with apraxia in response to verbal command of his left but not right hand (Geschwind & Kaplan, 1962). Fortunately, at that time, Fred Quadfasel was a staff neurologist at the Boston Veterans’ Hospital and often collaborated with Geschwind

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and Kaplan. Quadfasel had been trained by Kurt Goldstein, who, in turn, had been trained by Hugo Liepmann. Thus, when Geschwind and Kaplan informed Quadfasel about this case, he referred them to the works of Liepmann. These seminal papers had been forgotten for more than 40 years, and it was Geschwind and Kaplan’s interest in apraxia that induced a renaissance of interest in this common and disabling disorder. While the first author of this chapter (KMH) was a fellow at the Harvard Neurological Unit of Boston City Hospital, Derek Denny-Brown retired and Norman Geschwind replaced Denny-Brown as chief. It was Geschwind who first excited my (KMH) interest in apraxia. The first papers that I (KMH) wrote on apraxia were coauthored with Geschwind. During the time I was a fellow with Geschwind, I met and worked with another neurologist who was visiting from Italy, Luigi Vignolo. Although Luigi Vignolo remained interested in aphasia, it was apparent from our first meeting that he was destined to be one of the world’s leading behavioral neurologists.

Limb apraxia syndromes Limb-kinetic apraxia (melokinetic apraxia, innervatory apraxia) Clinical description According to Liepmann (1905, 1920), patients with limb-kinetic apraxia (LKA) have slow and stiff movements. He noted that when they attempt to perform a skilled act, their movements are coarse and clumsy. Kleist (1907) noted that people with this type of apraxia have a loss of independent finger movements, and also have problems coordinating simultaneous movements. As noted above, this loss of deftness or the ability to make finely graded, precise, rapid, and independent but coordinated finger movements has been termed by several names, but here we will call this disorder LKA. Testing Finger tapping can be used to test the speed of finger movements, and a pegboard task can be used to test precision. To assess a patient’s ability to perform independent finger movements, together with speed, precision, and coordination, we use the coin-rotation task (Hanna-Pladdy, Mendoza, Apostolos, & Heilman, 2002). In this coin-rotation task, the patient is asked to rotate a nickel between their thumb, index finger, and middle finger as rapidly as possible for 20 revolutions. The examiner measures the time it takes to complete this task and does not stop the clock if the nickel is dropped. Normal subjects demonstrate right-hand preference on this coin-rotation task. Normative data collected on the coin-rotation task (based on 60 male subjects) yielded a right-hand mean of 12.9 s (sd 2.5) and a left-hand mean of 14.5 s (sd 2.6) for task completion (Hanna-Pladdy et al., 2002). Both

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left-hemisphere (LHD) and right-hemisphere (RHD) stroke subjects displayed contralesional motor deficits, particularly on this coin-rotation task. This coin-rotation task might be the most sensitive test for LKA. In addition, unlike the finger-tapping and grooved-pegboard tests, the coin-rotation test can be used by clinicians at bedside, without having to carry additional apparatus. The classical definition of LKA includes loss of deftness for the hand contralateral to a hemispheric lesion. However, Heilman, Meador, and Loring (2000) and Hanna-Pladdy and colleagues (2002) have found that people with right-hand preference are more likely to have additional ipsilateral loss of deftness (LKA) following left- rather than right-hemispheric dysfunction. Possible mechanisms In his classical diagram, Liepmann (1920) illustrated that the location of the lesion that induces LKA includes the primary motor cortex (precentral cortex or Brodmann’s area 4), and the primary tactile sensory cortex (the postcentral gyrus or Brodmann’s areas 3, 2, and 1). Bucy and Keplinger (1960) treated patients with disabling abnormal movements by sectioning their contralateral corticospinal pathway in the cerebral peduncle and found that these patients were not hemiparetic, but did have a loss of hand deftness. These observations suggested that the corticospinal system might be important in deftness and that injury to this system induces LKA. Further support for this postulate came from the work of Lawrence and Kuypers (1968), who trained monkeys to retrieve food from different-sized wells. After sectioning the corticospinal tract in the brainstem pyramid, they noted that monkeys could retrieve food from the large wells with a palmer grasp, demonstrating that they were not terribly weak and knew the task. However, they could not retrieve food from the small wells because this required the monkey to use a pincher grasp. In the pincher grasp, only the forefinger and thumb are used, and the monkeys could not make these independent, precise finger movements. Lesions of the convexity premotor cortex might also be important for inducing this defect. In his apraxia diagram, Liepmann illustrates that the cortical areas, which, when injured, induce LKA, also include what appears to be the convexity of the premotor cortex (Brodmann’s area 6). The role of the convexity premotor cortex in LKA is not fully known, although the premotor neurons in this area connect to many portions of the primary motor cortex. Fogassi, Gallese, Buccino, Craighero, Fadiga, and Rizzolatti (2001) demonstrated that functional ablation of the ventral convexity premotor cortex induces a deficit in precision grasping, and Freund, together with Hummelsheim (1985), showed that damage to the premotor cortex is associated with LKA. In addition, Nirkko and coworkers (2001) studied these areas with fMRI and found that discrete unilateral distal finger movements were associated with activation of the convexity premotor cortex.

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Heilman and colleagues (2000), as well as Hanna-Pladdy and colleagues (2002), have demonstrated that right-handed patients with left-hemisphere dysfunction often have both ipsilateral and contralateral LKA. In contrast, patients with right-hemisphere dysfunction display LKA that is primarily limited to their left hand. These observations suggest that the left hemisphere might have stronger ipsilateral control of spinal motor neurons than the right hemisphere, and physiological studies appear to support this postulate. There are two possible means by which this ipsilateral control might be mediated: through ipsilateral corticospinal tract projections or by way of the interhemispheric commissures. Motor evoked potential studies using transcranial magnetic stimulation (TMS) have revealed that there are stronger ipsilateral connections from the left hemisphere to the left arm (MacKinnon, Quartarone, & Rothwell, 2004) than vice versa. However, these asymmetries primarily affect proximal muscles and the deftness defect, which is a characteristic of LKA, primarily involves the muscles that control distal movements. This finding suggests that in right-handed people, the left hemisphere’s ipsilateral control of distal movement might be primarily mediated by the cerebral commissures, most likely the corpus callosum. Support for this callosal postulate comes from the work of Gilio, Rizzo, Siebner, and Rothwell (2003), who demonstrated that repetitive TMS to the left hemisphere leads to an increase in corticospinal excitability in the right hemisphere’s motor cortex. Ideomotor apraxia Clinical description Patients with ideomotor apraxia (IMA) make primarily spatial and temporal production errors that cannot be attributed to a loss of deftness as described above. Spatial errors include postural (or internal configuration), spatial movement, and spatial orientation (Poizner, Mack, Verfaellie, Rothi, & Heilman, 1990; Rothi, Mack, Verfaellie, Brown, & Heilman, 1988). The test most likely to reveal these temporal and spatial errors is to ask patients to gesture ( pantomime) to verbal command. Patients with IMA often perform more poorly with transitive than intransitive acts (Haaland, Harrington, & Knight, 2000; Rothi et al., 1988). Although patients with IMA typically improve with imitation, their performance remains impaired. When using actual tools, their performance may improve even more, but even with the use of actual tools and implements their performance remains abnormal (Poizner et al., 1990). There are at least two postural errors that can be associated with IMA. Goodglass and Kaplan (1963) noted that when apraxic patients are asked to pantomime, they often use a body part as the tool. For example, when asked to pantomime using a pair of scissors instead of positioning their hands in the correct posture, they may use their fingers as if they were the blades.

166 Heilman, Gonzalez Rothi, Hanna-Pladdy Many normal subjects initially make similar errors, but patients with IMA are unlike normal subjects since these patients may continue using their body parts as tools in spite of instructions not to use their fingers as blades (Raymer, Maher, Foundas, Heilman, & Rothi, 1997). When not using their body parts as tools, patients with IMA often fail to correctly position their hands as if they were holding a tool or object. Patients’ ability to adopt correct postures can also be tested by having them imitate the examiner’s posture. Patients with apraxia frequently make configuration and body part errors as tool errors even when they are imitating (Haaland et al., 2000). When normal subjects are asked to use a tool (such as to slice turkey with a knife), they will orient the tool to an imaginary target of that tool’s action (e.g. the turkey). However, patients with IMA often fail to orient their forelimbs to an imaginary target (Poizner et al., 1990; Rothi et al., 1988) or to maintain this orientation when the pantomime calls for repeated actions (such as slicing). When patients with IMA attempt to perform a learned skilled movement, they often execute the correct core movement (e.g. twisting, pounding, cutting), but the way in which they move their forelimb through space is often incorrect (Poizner et al., 1990; Rothi et al., 1988). For example, when asked to slice turkey with a knife, they make vertical chopping movements rather than producing primarily horizontal (back-and-forth) slicing movements; or when asked to use a screwdriver, they form arcs rather than making movements so that the imagined shaft of the screwdriver stays on axis. Movements of the incorrect joints can cause these movement errors, and these incorrect joint movements are made because the patients contract the incorrect muscles. Thus, patients with IMA often stabilize a joint that they should be moving and move joints that should not be moving. For example, when attempting to pantomime using a screwdriver, they might fixate their elbow and shoulder joints and just move the wrist. Movements isolated to the wrist cause the patient’s hand to move in arcs rather than on axis. In addition, movement errors are also caused by these patients’ inability to coordinate multiple-joint movements. For example, when patients with IMA pantomime the act of slicing a turkey with a knife, as they bring their arm forward at the shoulder they often do not extend their forearm at the elbow. Hence, they make stabbing movements or they might alternatively flex–extend their forearm at the elbow when their arm is moving backward, thereby creating chopping movements. By computer analysis of apraxic patients’ movements, Poizner and coworkers (1990) noted that patients with IMA might also make timing errors, including a long delay before initiating a movement and brief multiple stops (stuttering movements). When normal subjects pantomime slicing, they reduce the speed of their movements as they are about to change the direction of the knife, and increase their speed when they move the imaginary knife in a straight line. However, patients with IMA do not demonstrate smooth sinusoidal hand speeds when pantomiming slicing movements.

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Testing GENERAL NEUROLOGICAL EXAMINATION

As mentioned above, the diagnosis of apraxia is in part a diagnosis of exclusion. Thus, before any form of apraxia can be diagnosed, the clinician should determine that the failure to perform purposeful motor acts cannot be entirely explained by elemental motor disorders such as weakness or movement disorders, sensory defects, or intellectual disorders that would prevent the patient from understanding the task. The presence of elemental motor disorders, sensory defects, and cognitive impairments (such as aphasia) does not preclude praxis assessment, but the examiner must interpret the results of praxis testing with the knowledge gained from the general neurological examination. FORELIMB TESTED

When one forelimb has an elemental or sensory disorder that would preclude testing, the nonparetic limb should be tested. Whenever possible, however, both forelimbs should be tested. GESTURE TO COMMAND

Patients should be requested to pantomime/gesture both transitive acts (e.g. “Show me how you would use scissors to cut a piece of paper in half ”) as well as intransitive acts (e.g. “Wave goodbye”). In general, patients with IMA have greater difficulty with transitive than intransitive gestures. GESTURE IMITATION

The patient should be asked to imitate the examiner performing both meaningless and meaningful gestures, both transitive and intransitive. GESTURE IN RESPONSE TO SEEING AND HOLDING ACTUAL TOOLS AND OBJECTS

Independent of the results of pantomime to command and imitation tests, the patient should also be allowed to demonstrate how to use actual tools or objects after viewing and holding these implements. The examiner may also show the patient objects upon which tools work (e.g. nail) and, without having the patient hold a tool or object, request that the patient pantomimes the action associated with that object.

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PANTOMIME RECOGNITION AND DISCRIMINATION

It may be valuable to see whether the patient can name or recognize transitive and intransitive pantomimes or postures made by the examiner, and discriminate between correctly and incorrectly performed pantomimes or postures that are performed by the examiner. Recently, Mozaz, Rothi, Anderson, Crucian, and Heilman (2002) developed a praxis-posture discrimination test that contains cartoons of people performing transitive and intransitive acts, and this test also can be used to test recognition. Patients with IMA have been noted to have more difficulty in performing transitive than intransitive gestures (Goodglass & Kaplan, 1963). The fact that patients with IMA have more problems gesturing transitive than intransitive movements might be related to differences in movement complexity, since transitive movements are often more complex than intransitive ones. Alternatively, the programs for intransitive gestures might be better defined, more widely distributed, or easier to activate than those for transitive pantomimes. To test these alternative hypotheses, Mozaz et al. (2002) studied normal subjects’ ability to discriminate between correct and incorrect transitive pantomimes and intransitive gestures. This discrimination was performed by having subjects look at cartoons of a person performing transitive or intransitive acts, but this person’s hand could not be seen. Below these cartoons, three hand postures were displayed, one correct and two foils. The subjects were instructed to point at the illustrations of correct hand postures. The subjects performed better when discriminating postures associated with intransitive gestures than the postures associated with transitive pantomimes. These results cannot be explained by complexity because the hand postures associated with the transitive versus intransitive gestures were equally complex. Thus, these results appear to refute the complexity hypothesis and provide support for the representational activation-hypothesis. Possible mechanisms In right-handed people, IMA is almost always associated with left-hemisphere lesions. However, in left-handed people IMA has been reported with righthemisphere lesions (Heilman & Coyle et al., 1973). IMA is associated with lesions in a variety of structures, including the corpus callosum, the inferior parietal lobe, and the premotor cortex (supplementary motor area (SMA) and the convexity premotor cortex). IMA has also been reported with subcortical lesions that involve the basal ganglia, the hemispheric white matter, and the thalamus. We will briefly discuss each of these anatomic areas. CORPUS CALLOSUM

Liepmann and Maas (1907) reported that a 70-year-old carpenter with a lesion of his corpus callosum was unable to correctly pantomime to commands with

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his left arm. Unfortunately, this patient also had a right hemiparesis from a pontine lesion, and so his right hand could not be tested. Since the work of Paul Broca, it has been known that the left hemisphere is dominant for mediating language, especially for those individuals with right-hand preference. Liepmann and Maas (1907) could have attributed their patient’s inability to pantomime to verbal command with his left hand, to a disconnection between language, which is mediated by the left hemisphere, and motor areas that control the left arm in the right hemisphere. However, Liepmann and Maas (1907) suggested that the left hemisphere of right-handed people contains movement formulas or memories of the spatial-temporal patterns required to make these skilled movements, and that the callosal lesion in this patient disconnected these movement formulas from the right hemisphere’s motor areas. Subsequently, Geschwind and Kaplan (1962), as well as Gazzaniga, Bogen, and Sperry (1967), also found that their patients with callosal disconnection could not correctly pantomime to command with their left hand. However, unlike the patient reported by Liepmann and Maas (1907), these patients could imitate and correctly use actual tools and objects with their left hand. The preserved ability to imitate and use actual tools and objects suggests that the inability to gesture to command in patients with callosal lesions was induced by a language–motor disconnection rather than a movement formula motor disconnection, as proposed by Liepmann and Maas. In addition, theoretically, a disconnection between movement formula stored in the left hemisphere and the motor areas of the right hemisphere should produce spatial and temporal errors, but many of the errors of the patient described by Liepmann and Maas appeared to be content errors. Watson and Heilman (1983), as well as Graff-Radford, Welsh, and Godersky (1987), described patients with infarctions limited to the corpus callosum. Watson and Heilman’s patient had no weakness in her right forelimb and performed tasks, such as pantomiming to command, imitation, and the use of actual objects, flawlessly with her right forelimb. As Liepmann and Maas might have predicted, however, with her left hand she could not correctly pantomime to command, imitate, or use actual tools. Like the patient described by Liepmann and Maas, immediately after her cerebral infarction she made content errors, but these types of errors diminished, and she subsequently made primarily spatial and temporal errors. Her performance indicated that not only language but also spatial-temporal movement representations (movement formula) were stored in her left hemisphere, and the callosal lesion disconnected these representations from her right hemisphere. LESIONS OF THE LEFT HEMISPHERE

Liepmann (1905) reported that of 42 patients with left hemiplegia from righthemisphere lesions, none were apraxic when using their ipsilesional right forelimb. In contrast, 20 of 41 with right-sided weakness from left-hemisphere

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lesions were apraxic when using their ipsilesional left forelimb. Based on these observations, as well as the report of the patient with a callosal lesion mentioned above, Liepmann concluded that in right-handed patients the left hemisphere has a special role in mediating skilled movements. Many patients with left-hemisphere lesions who present with IMA are also aphasic. Shortly after Steinthal (1871) described and used the term “apraxia”, Finkelburg (1873) suggested that apraxia is a form of asymbolia. Hence, aphasia might be explained as an inability to use verbal signs, and apraxia as an inability to use gestural signs. However, Liepmann noted that aphasia and apraxia are dissociable, some apraxic patients having no aphasia and some aphasic patients do not demonstrate apraxia. These dissociations provide evidence against the postulate that apraxia is a form of asymbolia. More recently, Papagno, Della Sala, and Basso (1993) demonstrated the same dissociation. PARIETAL LOBE

Although he originally considered the supramarginal gyrus of the left parietal lobe to be the site storing the “movement formulas” or spatial-temporal movement representations, Liepmann (1920) later denied believing that there were praxis centers and proposed that white-matter tracts below the supramarginal gyrus carry information about the nature of the desired movements. As mentioned in the history section, after reading Liepmann’s papers, Norman Geschwind became aware that the left-hemisphere lesions most commonly associated with IMA were located in the region of the supramarginal gyrus of the left parietal lobe. In order to explain why lesions in this region induce IMA of both hands, he stated that the lesions in the left hemisphere could induce a disconnection syndrome (Geschwind, 1965). Thus, when a patient is given a command to perform a gesture, the incoming verbal message is decoded in Wernicke’s area, but this message must then be transmitted to the left premotor convexity cortex for the command to be implemented by the left primary motor cortex. According to Geschwind, if the command is to use the left hand to gesture, the left premotor cortex transmits this information to the right hemisphere’s motor systems. The Liepmann–Geschwind disconnection hypothesis could not account for the observation that patients with apraxia resulting from left parietal lesions are also impaired when imitating and even when using actual objects with their left forelimb, because their right-hemispheric connections (between the anterior motor areas and the posterior visual areas) are intact. To help explain the lack of dissociation between verbal commands and imitation or actual object use, Heilman, Rothi, and Valenstein (1982) and Rothi, Heilman, and Watson (1985) proposed that the movement representations of right-handed individuals are stored in the left parietal lobe. Therefore, destruction of the left parietal lobe should produce both a production deficit (apraxia) and a gesture/pantomime comprehension/discrimination disorder. In contrast, apraxia induced by each of the following lesions might

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cause just a production deficit: (1) premotor lesions, (2) lesions in the pathways that connect the premotor cortex to primary motor cortex, and (3) lesions to the pathways that lead to the premotor areas from the parietal lobe. However, unlike parietal lesions that destroy the movement representations, these more anterior lesions should not induce gesture comprehension and discrimination disorders. Heilman et al. (1982) and Rothi et al. (1985) tested patients with anterior and posterior lesions and found that while both groups of patients were apraxic (had production deficits), the patients with a damaged parietal lobe (unlike those with frontal damage) had comprehension and discrimination disturbances. Halsband, Schmitt, Weyers, Binkofski, Grutzner, and Freund (2001) attempted to replicate these findings, stating: Taken together, these findings support Heilman’s model of apraxia . . . that apraxia results from destruction of spatiotemporal representations of learned movements. . . . In order to perform a skilled learned act, one must place particular body parts in certain spatial positions in a specific order at specific times. This implies that the nervous system stores knowledge of motor skills. When this knowledge is called into use, it is retrieved from motor memory rather than being constructed de novo. According to Heilman’s model, spatiotemporal representations of learned, skilled movements are stored in the parietal cortex which is thought to instruct the premotor cortex for the necessary movements. In addition to the report by Halsband and colleagues (2001), Haaland et al. (2000) performed a lesion localization study on patients with and without apraxia. They found that, in addition to frontal convexity lesions, patients most often have lesions in the region of the intraparietal sulcus, which is at the top of the supramarginal gyrus, and in the superior parietal lobe (Brodmann’s area 7). In regard to Geschwind’s disconnection hypothesis, Haaland et al. (2000) found that 49% of their subjects had subcortical damage that disconnected the pathways between the occipital and frontal cortex, but yet performed imitation normally. The results of the Basso, Luzzatti, and Spinnler (1980) study also provided evidence against the disconnection hypothesis of IMA. Finally, recent functional imaging studies performed with normal right-handed subjects, provide converging evidence that the parietal lobe plays a critical role in the production of skilled movements (Moll et al., 2000; Rumiati et al., 2004). SUPPLEMENTARY MOTOR AREA (SMA)

For each skilled movement, parts of the forelimb must traverse a set of spatial loci in a specific temporal pattern. For example, during the upswing in hammering, the arm should be flexed at the elbow and the wrist extended, while on the downswing the forearm is extended at the elbow while the wrist is

172 Heilman, Gonzalez Rothi, Hanna-Pladdy flexed. At the same time that this flexion and extension occurs, the arm should be kept in the same radial plane (e.g. sagittal plane). We have proposed that movement formula representations, stored in the inferior parietal lobe, are represented in a three-dimensional supramodal (temporal visual-spatial and temporal kinesthetic-spatial) code. In order for the corticospinal neurons to properly activate the anterior horn cells in the spinal cord, this stored spatial-temporal movement knowledge has to be transformed into a motor program. The medial premotor cortex, including the SMA, the cingulate motor areas, and perhaps the pre-SMA, appear to play an important role in mediating skilled movements. In man, it has been shown that electrical stimulation of the primary motor cortex induces simple movements, but SMA stimulation induces complex movements that may include the entire forelimb (Penfield & Welch, 1951). The SMA receives projections from parietal neurons and projects directly to both the motor cortex (Brodmann’s area 4) and to the convexity premotor cortex. In addition, the SMA projects to the basal ganglia (to be discussed in a subsequent section) as well as to the motor neurons in the spinal cord. Supplementary motor neurons discharge before neurons in the primary motor cortex. Studies of cerebral blood flow, an indicator of cerebral metabolism and synaptic activity, have revealed that single repetitive movements increase activation of the contralateral primary motor cortex, whereas complex movements increase flow in the contralateral motor cortex and the SMA (Lauritzen, Henriksen, & Lassen, 1981; Rao et al., 1993). When subjects remain still and think about making complex movements, blood flow is increased to the SMA, but not the primary motor cortex. Watson, Fleet, Rothi, and Heilman (1986) reported several patients with leftsided medial frontal lesions that included the SMA who demonstrated IMA when tested with either arm. Unlike patients with parietal lesions, these patients could both comprehend and discriminate between correctly and incorrectly performed pantomimes. Studies of patients with corticobasal degeneration with IMA suggest that part of their deficit might also be related to SMA dysfunction (Leiguardia, Lees, Merello, Starkstein, & Marsden, 1994). In Haaland et al.’s (2000) study of lesion sites associated with IMA, the authors did not identify left medial frontal lesions, including SMA, as critical. However, strokes in the distribution of the anterior cerebral artery are much less common than those in the middle cerebral artery, and these investigators’ findings might be related to a sampling bias. In addition, the investigators tested their patients by an imitation task. In the speech domain, patients with medial frontal lesions are very often nonfluent but repeat normally, and it is possible that the imitation test is not the proper means of detecting IMA that might be associated with medial frontal lesions.

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CONVEXITY PREMOTOR CORTEX

Liepmann (1920) did not think that lesions of the convexity premotor cortex induce IMA, but in Geschwind’s (1965) disconnection model the convexity premotor cortex appears to play a critical role. In an excellent review of apraxia, Faglioni and Basso (1985) commented that “the unanimous acceptance of the crucial role played by the premotor cortex in practice functioning by so many authors is, however, a bit surprising when one considers how hard it is to find in the literature well documented cases of apraxia from lesions confined to this area.” Kolb and Milner (1981) did report that patients with frontal premotor excisions have difficulty in imitating motor sequences, and, recently, there have been some other reports that lesions restricted to this region might induce IMA (Barrett, Schwartz, Raymer, Crucian, Rothi, & Heilman, 1998; Haaland et al., 2000). Barrett et al. (1998) suggested that the premotor cortex might be important in coordinating several joint movements. These authors also suggested that different portions of the premotor cortex (convexity versus medial) might implement two different types of innervatory patterns. Whereas the medial portion might be important in top-down or offline-prepared programs, the convexity might be more important in bottomup or online programs that require sensory feedback to guide movement. Goldberg (1985) also suggested that since the convexity premotor cortex receives projections from the visual association areas, this area might be the portion of the premotor cortex that is important in mediating externally (visually) controlled movements. The patient reported by Barrett et al. (1998), with a convexity premotor cortex lesion, had normal comprehension/ discrimination of gestures, but gesturing-pantomiming was severely impaired. On further testing, Barrett’s patient could execute correct isolated movements and even sequential movements, but she could not coordinate simultaneous movement of more than one joint. However, even though she had a convexity premotor lesion, she did not appear to have a specific deficit in bottom-up or online movements as would be expected from Goldberg’s hypothesis. However, these hypotheses need to be further tested. Haaland et al. (2000) used the lesion overlap method for localization of premotor lesions that are associated with IMA. They found that the middle frontal gyrus appeared to be the critical area. However, Freund and Hummelsheim (1985) studied a population of patients with convexity premotor lesions and found that these patients had LKA, but not IMA. In addition, Haaland et al. (2000), as well as Kolb and Milner (1981), studied patients who had to produce imitations. Imitation, especially of novel gestures, requires working memory, and performance on this task might also be more dependent on visual kinesthetic feedback. Thus, the defect these investigators found in their subjects with convexity premotor lesions might have been related to either a working memory deficit or the fact that imitation of meaningless gestures is heavily dependent on sensory feedback.

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BASAL GANGLIA AND THALAMUS

As we discussed above, IMA is most often associated with lesions of the cerebral cortex as well as cortical-cortical connecting pathways such as the corpus callosum, but there have been reports of apraxia associated with subcortical lesions (e.g. Agostoni, Coletti, Orlando, & Tredici, 1983; Kertesz & Ferro, 1984; Kleist, 1907; von Monakow, 1914). After reviewing these cases, however, Faglioni and Basso (1985) concluded, “In fact, no convincing case report has ever been published in support of this association.” Following Faglioni and Basso’s review, other studies of apraxia in patients with subcortical lesions have been reported (Basso & Della Sala, 1986; Della Sala, Basso, Laiacona, & Papagno, 1992; De Renzi, Faglioni, Scarpa, & Crisi, 1986). However, after these reports, Pramstaller and Marsden (1996) performed a meta-analysis of 82 cases of “deep” apraxia reported in the literature. These reports were subdivided into those with small isolated lesions that involved nuclei of the basal ganglia only, those with pure, subcortical white-matter injury, and those with both. The main conclusion that these authors drew from this meta-analysis was that lesions confined to the basal ganglia (putamen, caudate nucleus, and globus pallidus) rarely, if ever, cause apraxia. In many of these studies of IMA associated with subcortical lesions, subjects were assessed only by means of imitation, and data were quantitatively analyzed. Since the use of tests such as pantomime to command and qualitative analysis of errors might better elucidate the role of the basal ganglia in the production of learned skilled movements, Hanna-Pladdy, Heilman, and Foundas (2001) studied a population of patients with both cortical and subcortical strokes and compared praxis performance on a variety of tasks. The patients with cortical injury presented with deficits in the production of transitive pantomimes and intransitive gestures-to-verbal command as well as imitation. These patients also had impaired gesture discrimination. The patient group with subcortical injury, however, demonstrated only mild production-execution deficits for transitive pantomimes to command, but improved on imitation and discrimination. The subcortical group showed more postural errors whereas patients with cortical lesions produced more sequencing and content errors. These behavioral dissociations suggest that subcortical structures provide an independent contribution to the praxis processing system. In regard to the thalamus, several case reports of patients who developed apraxia from lesions of the left thalamus have been published (Nadeau, Roeltgen, Sevush, Ballinger, & Watson, 1994; Shuren, Maher, & Heilman, 1994). The reason why thalamic damage induced apraxia in these patients is not known, but they had involvement of the pulvinar nucleus. The pulvinar nucleus is strongly connected with the parietal lobes, and injury to this nucleus might interrupt normal parietal lobe function and consequently it may be critical in the control of purposeful, skilled movements.

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Dissociation apraxia Clinical observations Heilman (1973) described patients who, when asked to pantomime to command, looked at their hand but failed to perform any recognizable actions. Unlike patients with IMA, these patients’ imitation and use of objects were flawless. In addition, when they saw the tool or object they were also able to pantomime flawlessly. De Renzi, Faglioni, and Sorgato (1982) reported not only patients similar to those reported by Heilman (1973), but also patients who showed a similar defect in other modalities. For example, when asked to pantomime in response to visual or tactile stimuli, some patients were unable to do so, but these patients could pantomime to verbal command. Testing The tests used to assess patients for dissociation apraxia are similar to those used to assess patients for IMA. The most important part of this testing is to determine whether there are any modality-specific differences when the patient pantomimes in response to verbal command, seeing the tool-implement, or holding but not seeing the tool or implement. Possible mechanisms As we discussed above, lesions that induce an interhemispheric disconnection by damaging the corpus callosum may cause IMA, in which patients are unable to correctly pantomime, imitate, or use actual objects with their nonpreferred left hand. Some patients with callosal disconnection, however, might demonstrate dissociation apraxia where they fail to correctly pantomime to command with their nonpreferred left hand, but are able to correctly imitate and use actual objects. For example, the callosally disconnected patients described by Geschwind and Kaplan (1962) presented with dissociation apraxia of their left hand. With their left hand, they could not gesture normally to command but performed well on imitation and used actual tools and objects normally. To explain dissociation apraxia in these patients, we proposed that whereas language is mediated by their left hemisphere, movement representations ( praxicons) are stored bilaterally. Therefore, their callosal lesion induced a dissociation apraxia only of the left hand because the verbal command could not get access to the movement representations in the right hemisphere. Whereas these patients with callosal dissociation apraxia were not be able to correctly carry out skilled learned movements of the left arm to command, they could imitate and use actual tools or implements with their left hand. Using actual objects and imitating do not need verbal mediation, and the movement representations stored in their right hemisphere can be activated by visual or tactile input.

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Right-handed patients who have both language and movement formula represented in their left hemisphere may show a combination of dissociation apraxia and IMA associated with callosal lesions (Watson & Heilman, 1983). When asked to pantomime with their left hands, they may look at them and perform no recognizable movement (dissociation apraxia), but when imitating or using actual tools and objects, they may demonstrate spatial and temporal errors as observed in IMA. Dissociation apraxia might also be associated with left-hemisphere lesions. The patients reported by Heilman (1973) and De Renzi et al. (1982) probably had intrahemispheric, language-movement formula dissociation, visionmovement formula dissociation, or somesthesic-movement formula dissociation, such that, depending on the type of dissociation, stimuli from one of these modalities (such as language) cannot activate the movement representations, but stimuli in other modalities (such as vision) can activate these representations. The anatomical loci of the lesions that cause this intrahemispheric dissociation apraxia are not known but the advent of diffusion tensor imaging might help inform investigators of the localization of the injuries that induce these disorders. Ideational apraxia Clinical observations The inability to perform a series of acts, an ideational plan, has been called ideational apraxia (Marcuse, 1904; Pick, 1905). Pick’s patient, however, produced two types of errors. One error was characterized by incorrect use of objects. Although patients with IMA might incorrectly use actual objects, their errors are usually production errors (postural, temporal, or spatial), but Pick’s patient used objects for purposes for which these tools or implements were not designed; for example, using a razor as a comb (Brown, 1972). Hence, this patient’s errors were conceptual. In addition, when performing a task that requires a series of acts, Pick’s patient (Brown, 1972) had difficulty in performing the sequence of acts needed to properly complete the task. Unfortunately, since Pick’s report, the term “ideational apraxia” has been erroneously used to label other disorders. For example, Heilman (1973) used this term when he first described dissociation apraxia. It was thought that patients with IMA performed normally with actual tools. Thus, when production errors with actual tools were observed, some clinicians thought that this inability to demonstrate how the tool is used, might be indicative of ideational apraxia (De Renzi & Lucchelli, 1988). Although patients with IMA usually improve when using actual tools and objects, they still may produce errors (Poizner et al., 1990). Although the inability to use actual tools and implements might also be associated with a conceptual disorder, patients with a severe production disorder might appear to have a conceptual-ideational

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disorder because they are unable to demonstrate how tools are used (Zangwill, 1960). As mentioned above, the term “ideational apraxia” has been used to describe patients who make conceptual errors. However, to distinguish this form of apraxia from those patients who fail to sequence a series of acts correctly, we term this former disorder “conceptual apraxia”. We reserve the term “ideational apraxia” to refer to the inability to perform a sequence of acts that lead to a goal, such as making a sandwich, consistent with Liepmann’s (1920) reference to a sequencing disorder or ideational plan. Testing The most important test for diagnosing ideational apraxia is having the patient perform a task that requires several sequential motor acts (as in making a sandwich). Possible mechanisms Most of the patients with this type of ideational apraxia suffer from degenerative dementia. However, Liepmann (1920) and others suspected that the lesion that induced this disorder was localized in the left occipital parietal region. The support for this localization, however, has not been strong. Focal injury to the frontal lobes is often also associated with temporal order processing deficits. For example, disorders of verbal syntax in which there are word-ordering defects, are most often associated with anterior aphasia such as Broca’s aphasia. In addition, when patients with frontal lesions are asked to recall a series of objects, they might be able to recall these objects, but not in the order in which they were presented. Hence, the critical focus of dysfunction in ideational apraxia might be in frontal-subcortical systems. Although there is some support for this postulate (Humphreys & Forde, 1998), more research is needed. Conceptual apraxia Clinical observations To perform a skilled act, two types of knowledge are needed: conceptual knowledge and production knowledge. Whereas dysfunction of the praxis production system induces IMA, defects in the knowledge needed to select tools and perform the correct action with these tools is termed “conceptual apraxia”. Therefore, patients with IMA make production errors (such as spatial and temporal errors), and patients with conceptual apraxia make content and tool selection errors. Patients with conceptual apraxia make these errors because they may not recall the type of actions associated with specific tools, utensils, or objects (tool–object action associative knowledge)

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(De Renzi & Lucchelli, 1988; Ochipa, Rothi, & Heilman, 1989). For example, when asked to demonstrate the use of a screwdriver by either pantomiming or using the tool, the patient with loss of tool–object action knowledge may pantomime a hammering movement or use the screwdriver as if it were a hammer. Content errors (using a tool as if it were another tool) can also be induced by object agnosia. However, Ochipa et al. (1989) reported a patient who could name tools (and therefore did not display agnosia) but often used these tools inappropriately. Patients with conceptual apraxia may be unable to recall which specific tool is associated with a specific object (tool–object associative knowledge). For example, when shown a partially driven nail, they may select a screwdriver rather than a hammer. This conceptual defect may also be present in the verbal domain such that when an actual tool is shown to a patient, the patient may be able to name it (e.g. hammer). However, a patient with conceptual apraxia may not be able to correctly point to or name a tool when its function is described. In addition, these patients may be unable to describe the functions of tools or demonstrate them with impaired mechanical knowledge. For example, if they are attempting to drive a nail into a piece of wood and there is no hammer available, they may select a screwdriver rather than a wrench or pliers (which are hard, heavy, and good for pounding) (Ochipa, Rothi, & Heilman, 1992). Mechanical knowledge is also important for tool development. Patients with conceptual apraxia may also be unable to correctly develop tools (Ochipa et al., 1992). Testing When we test patients for conceptual apraxia, at least three types of tests might be useful. When assessing tool–object knowledge, the examiner attempts to learn whether patients can match tools with the objects upon which tools operate (for example, given a partially driven nail, will they select a hammer, and vice versa (Schwartz et al., 2000). In contrast, when we assess associative tool–action knowledge, we might ask the patient to pantomime to command or view tools or even hold tools, and then determine whether the patient makes content errors (such a making a pounding motion with a screwdriver). The examiner might also attempt to learn whether the patient can match a specific tool (from a series of tools) with an action that is performed with that tool. To assess mechanical knowledge, the examiner might want to learn whether the patient knows the mechanical advantage that tools afford. This assessment can be performed by having the patient substitute or even fabricate tools to solve mechanical problems. For example, if there is a nail that needs to be pounded into a piece of wood and there is no hammer to complete the job, will the patient select a wrench or a screwdriver to finish pounding the nail into the wood?

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Possible mechanisms Liepmann (1920) thought that mechanical conceptual knowledge was located in the caudal parietal lobe, whereas De Renzi and Lucchelli (1988) localized it to the temporal-parietal junction. The patient reported by Ochipa et al. (1989) was left-handed and rendered conceptually apraxic by a lesion in the right hemisphere, suggesting that both production and conceptual knowledge have lateralized representations and that such representations are contralateral to the preferred hand. Further evidence that these conceptual representations are stored in the hemisphere contralateral to the preferred hand was derived from the observation of a patient who had a callosal disconnection and demonstrated conceptual apraxia of the nonpreferred (left) hand (Watson & Heilman, 1983). Heilman, Maher, Greenwald, and Rothi (1997) studied right-handed patients who had either right- or left-hemisphere cerebral infarctions, and found that conceptual apraxia was more commonly associated with left- than right-hemisphere injury. However, no specific anatomical region appeared to be critical, suggesting that mechanical knowledge may be widely distributed in the left hemisphere of right-handed people. Although conceptual apraxia may be associated with focal brain damage, it is perhaps most commonly seen in degenerative dementia of the Alzheimer type (Ochipa et al., 1992). Ochipa and coworkers also noted that the severity of conceptual apraxia and IMA do not always correlate. The observation that patients with IMA may not demonstrate conceptual apraxia and patients with conceptual apraxia may not demonstrate IMA supports the postulate that praxis production and praxis conceptual systems are independent. However, for normal function, these two systems must interact.

Conclusions We have described the clinical characteristics that define five forms of forelimb apraxia: limb-kinetic, ideomotor, dissociation, ideational, and conceptual. We have also discussed the possible neuropsychological mechanisms that may account for these cognitive motor disorders. Based on this information, we have developed an anatomically distributed modular network that is responsible for mediating skilled movements. In this model, movement (temporalspatial) representations are stored in the left parietal lobe. Injury to these representations induces IMA, such that when patients attempt to perform learned, purposeful movements, they make spatial (postural, orientation, and joint movement) and temporal errors. Because these representations are disrupted, these patients are also impaired at discriminating spatialtemporal errors. These movement representations have to be activated from input coming from language, visual, or kinesthetic systems, and if one of these systems cannot activate these movement representations, there is a modality-specific deficit in performing these learned skilled acts, called dissociation apraxia. Once activated by either visual systems or language

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networks, the visuospatial-kinesthetic information stored in these networks is transferred to the premotor cortex so that innervatory patterns can be developed. Injury to the systems that develop these innervatory patterns, based on input from the movement representations, also induces IMA. In contrast to patients with injured movement representations, patients with premotor injuries are not impaired at discriminating spatial-temporal errors. The innervatory pattern must be implemented by the motor cortex, which activates the motor neurons in the spinal cord. In patients with LKA, injury is located in the motor cortex and perhaps also in portions of the premotor cortex. These injuries interfere with the ability to make precise and coordinated independent finger and hand movements. When people see that an action is needed, they must decide what tool can best complete that action. They must also know what action that tool performs. When the correct tool is not available or a new tool is needed, they also need to know the mechanical advantage that tools afford and how this could be accomplished by alternatives. A loss of this knowledge is called conceptual apraxia. In right-handed people, this knowledge is stored in the left hemisphere, but the exact locations of these representations are unknown. Finally, the completion of a task sometimes requires that a series of independent acts be performed in a specific temporal sequence. An inability to sequence correctly a series of acts to achieve a goal is called ideational apraxia, and this deficit might be related to frontal-executive dysfunction.

References Agostoni, E., Coletti, A., Orlando, G., & Tredici, G. (1983). Apraxia in deep cerebral lesions. Journal of Neurology, Neurosurgery, and Psychiatry, 46, 804–808. Barrett, A. M., Schwartz, R. L., Raymer, A. L., Crucian, G. P., Rothi, L. J. G., & Heilman, K. M. (1998). Dyssynchronous apraxia: Failure to combine simultaneous preprogrammed movements. Cognitive Neuropsychology, 15, 685–703. Basso, A., & Della Sala, S. (1986). Ideomotor apraxia arising from a purely deep lesion [letter]. Journal of Neurology, Neurosurgery, and Psychiatry, 49, 437–454. Basso, A., Luzzatti, C., & Spinnler, H. (1980). Is ideomotor apraxia the outcome of damage to well-defined regions of the left hemisphere? Neuropsychological study of CAT correlation. Journal of Neurology, Neurosurgery, and Psychiatry, 43, 118–126. Brown, J. (1972). Aphasia, apraxia and agnosia: Clinical and theoretical aspects. Springfield, IL: C. C. Thomas. Bucy, P. C., & Keplinger, J. E. (1960). Section of the cerebral peduncles. TransAmerican Neurology Association, 85, 65–66. Della Sala, S., Basso, A., Laiacona, M., & Papagno, C. (1992). Subcortical localization of ideomotor apraxia: A review and an experimental study. In G. Vallar, S. F. Cappa, & C.-W. Wellesch, (Eds.), Neuropsychological disorders associated with subcortical lesions (pp. 357–380). Oxford: Oxford University Press. De Renzi, E., Faglioni, P., Scarpa, M., & Crisi, G. (1986). Limb apraxia in patients with damage confined to the left basal ganglia and thalamus. Journal of Neurology, Neurosurgery, and Psychiatry, 49, 1030–1038.

10. The forelimb apraxias

181

De Renzi, E., Faglioni, P., & Sorgato, P. (1982). Modality-specific and supramodal mechanisms of apraxia. Brain, 105, 301–312. De Renzi, E., & Lucchelli, F. (1988). Ideational apraxia. Brain, 111, 1173–1185. Faglioni, P., & Basso, A. (1985). Historical persective on apraxia. In E. A. Roy (Ed.), Neuropsychological studies of apraxia and related disorders (pp. 2–44). New York: North Holland Press. Finkelburg, F. (1873). Über Aphasie und Aysombolie nebst Versuch einer Theorie der Sprachbildung. Archive für Psychiatrie, 6. Fogassi, L., Gallese, V., Buccino, G., Craighero, L., Fadiga, L., & Rizzolatti, G. (2001). Cortical mechanism for the visual guidance of hand-grasping movements in the monkey: A reversible inactivation study. Brain, 124, 571–586. Freund, H. J., & Hummelsheim, H. (1985). Lesions of premotor cortex in man. Brain, 108, 697–733. Gazzaniga, M., Bogen, J., & Sperry, R. (1967). Dyspraxia following diversion of the cerebral commisures. Archives of Neurology, 16, 606–612. Geschwind, N. (1965). Disconnection syndromes in animals and man. Brain, 88, 237–294; 585–644. Geschwind, N., & Kaplan, E. (1962). A human cerebral deconnection syndrome. A preliminary report. Neurology, 12, 675–685. Gilio, F., Rizzo, V., Siebner, H. R., & Rothwell, J. C. (2003). Effects on the right motor hand-area excitability produced by low-frequency rTMS over human contralateral homologous cortex. Journal of Physiology, 551, 563–573. Goldberg, G. (1985). Supplementary motor area structure and function: Review and hypotheses. Behavioral and Brain Sciences, 8, 567–616. Goldstein, K. (1970). Hugo Karl Liepmann. In W. Haymaker & F. Schiller (Eds.), The founders of neurology (pp. 473–475). Springfield, IL: Charles C. Thomas. Goodglass, H., & Kaplan, E. (1963). Disturbance of gesture and pantomime in aphasia. Brain, 86, 703–720. Graff-Radford, N. R., Welsh, K., & Godersky, J. (1987). Callosal apraxia. Neurology, 37, 100–105. Haaland, K. Y., Harrington, D. L., & Knight, R. T. (2000). Neural representations of skilled movement. Brain, 123, 2306–2313. Halsband, U., Schmitt, J., Weyers, M., Binkofski, F., Grutzner, G., & Freund, H. J. (2001). Recognition and imitation of pantomimed motor acts after unilateral parietal and premotor lesions: A perspective on apraxia. Neuropsychologia, 39, 200–216. Hanna-Pladdy, B., Heilman, K. M., & Foundas, A. L. (2001). Cortical and subcortical contributions to ideomotor apraxia: Analysis of task demands and error types. Brain, 124, 2513–2527. Hanna-Pladdy, B., Mendoza, J. E., Apostolos, G. T., & Heilman, K. M. (2002). Lateralised motor control: Hemispheric damage and the loss of deftness. Journal of Neurology, Neurosurgery, and Psychiatry, 73, 574–577. Heilman, K. M. (1973). Ideational apraxia—a re-definition. Brain, 96, 861–864. Heilman, K. M., Coyle, J. M., Gonyea, E. F., & Geschwind, N. (1973). Apraxia and agraphia in a left-hander. Brain, 96, 21–28. Heilman, K. M., Maher, L. M., Greenwald, M. L., & Rothi, L. J. R. (1997). Conceptual apraxia from lateralized lesions. Neurology, 49, 457–464. Heilman, K. M., Meador, K. J., & Loring, D. W. (2000). Hemispheric asymmetries of limb-kinetic apraxia: A loss of deftness. Neurology, 55, 523–526.

182

Heilman, Gonzalez Rothi, Hanna-Pladdy

Heilman, K. M., Rothi, L. J. G., & Valenstein, E. (1982). Two forms of ideomotor apraxia. Neurology, 32, 415–426. Humphreys, G. W., & Forde, E. M. E. (1998). Disordered action schema and action disorganization syndrome. Cognitive Neuropsychology, 15, 771–811. Kertesz, A., & Ferro, J. M. (1984). Lesion size and location in ideomotor apraxia. Brain, 107, 921–933. Kleist, K. (1907). Kortikale (innervatorische) Apraxie. Jahrbuch für Psychiatrie und Neurologie, 28, 46–112. Kolb, B., & Milner, B. (1981). Performance of complex arm and facial movements after focal brain lesions. Neuropsychologia, 19, 491–503. Lauritzen, M., Henriksen, L., & Lassen, N. A. (1981). Regional cerebral blood flow during rest and skilled hand movements by xenon-133 inhalation and emission computerized tomography. Journal of Cerebral Blood Flow and Metabolism, 1, 385–389. Lawrence, D. G., & Kuypers, H. G. (1968). The functional organization of the motor system in the monkey. II. The effects of lesions of the descending brain-stem pathways. Brain, 91, 15–36. Leiguarda, R., Lees, A. J., Merello, M., Starkstein, S., & Marsden, C. D. (1994). The nature of apraxia in corticobasal degeneration. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 455–459. Liepmann, H. (1905). Die linke Hemisphäre und das Handeln. Münchener Medizinische Wochenschrift, 49, 2322–2326; 2375–2378. Liepmann, H. (1920). Apraxia. Ergebnisse der Gesamten Medizin, 1, 516–543. Liepmann, H., & Maas, O. (1907). Fall von linksseitiger Agraphie und Apraxie bei rechsseitiger Lähmung. Zeitschrift für Psychologie und Neurologie, 10, 214– 227. MacKinnon, C. D., Quartarone, A., & Rothwell, J. C. (2004). Inter-hemispheric asymmetry of ipsilateral corticofugal projections to proximal muscles in humans. Experimental Brain Research, 157, 225–233. Marcuse, H. (1904). Apraktische Symptome bei einen Falle von seniler Demenz. Zentralblatt für Neurologie, 15, 737–751. Moll, J., de Oliviera-Souza, R., Passman, L. J., Cunha, F. C., Souza-Lima, F., & Andreiuolo, P. A. (2000). Functional MRI correlates of real and imagined tool-use pantomimes. Neurology, 54, 1331–1336. Mozaz, M., Rothi, L. J., Anderson, J. M., Crucian, G. P., & Heilman, K. M. (2002). Postural knowledge of transitive pantomimes and intransitive gestures. Journal of the International Neuropsychology Society, 8, 958–962. Nadeau, S. E., Roeltgen, D. P., Sevush, S., Ballinger, W. E., & Watson, R. T. (1994). Apraxia due to a pathologically documented thalamic infarction. Neurology, 44, 2133–2137. Nirkko, A. C., Ozdoba, C., Redmond, S. M., Burki, M., Schroth, G., Hess, C. W., et al. (2001). Different ipsilateral representations for distal and proximal movements in the sensorimotor cortex: Activation and deactivation patterns. NeuroImage, 13, 825–835. Ochipa, C., Rothi, L. J. G., & Heilman, K. M. (1989). Ideational apraxia: A deficit in tool selection and use. Annals of Neurology, 25, 190–193. Ochipa, C., Rothi, L. J. G., & Heilman, K. M. (1992). Conceptual apraxia in Alzheimer’s disease. Brain, 114, 2593–2603. Papagno, C., Della Sala, S., & Basso, A. (1993). Ideomotor apraxia without aphasia

10. The forelimb apraxias

183

and aphasia without apraxia: The anatomical support for a double dissociation. Journal of Neurology, Neurosurgery, and Psychiatry, 56, 286–289. Penfield, W., & Welch, K. (1951). The supplementary motor area of the cerebral cortex. Archives of Neurology and Psychiatry, 66, 289–317. Pick, A. (1905). Studien über motorische Apraxia und ihr nahestenhende Erscheinungen. Leipzig: Deuticke. Poizner, H., Mack, L., Verfaellie, M., Rothi, L. J. G., & Heilman, K. M. (1990). Three dimensional computer graphic analysis of apraxia. Brain, 113, 85–101. Pramstaller, P. P., & Marsden, C. D. (1996). The basal ganglia and apraxia. Brain, 119, 319–340. Rao, S. M., Binder, J. R., Bandettini, B. S., Hammeke, T. A., Yetkin, F. Z., Jesmanowicz, A., et al. (1993). Functional magnetic resonance imaging of complex human movements. Neurology, 43, 2311–2318. Raymer, A. M., Maher, L. M., Foundas, A. L., Heilman, K. M., & Rothi, L. J. G. (1997). The significance of body part as tool errors in limb apraxia. Brain and Cognition, 34, 287–292. Rothi, L. J. G., Heilman, K. M., & Watson, R. T. (1985). Pantomime comprehension and ideomotor apraxia. Journal of Neurology, Neurosurgery, and Psychiatry, 48, 207–210. Rothi, L. J. G., Mack, L., Verfaellie, M., Brown, P., & Heilman, K. M. (1988). Ideomotor apraxia: Error pattern analysis. Aphasiology, 2, 381–387. Rumiati, R. I., Weiss, P. H., Shallice, T., Ottoboni, G., Noth, J., Zilles, K., et al. (2004). Neural basis of pantomiming the use of visually presented objects. NeuroImage, 21, 1224–1231. Schwartz, R. L., Adair, J. C., Raymer, A. M., Williamson, D. J. G., Crosson, B., Rothi, L. J. G., et al. (2000). Conceptual apraxia in probable Alzheimer’s disease as demonstrated by the Florida Action Recall Test. Journal of the International Neuropsychology Society, 6, 65–70. Shuren, J. E., Maher, L. M., & Heilman, K. M. (1994). Role of the pulvinar in ideomotor praxis. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 1282–1283. Steinthal, P. (1871). Abriss der Sprachwissenschaft. Berlin: Harriwitz and Gossmann. von Monakow, C. (1914). Die Lokalisation im Grosshirn und der Abbau der Funktion durch kortikale Herde. Wiesbaden: Bergmann. Watson, R. T., Fleet, W. S., Rothi, L. J. G., & Heilman, K. M. (1986). Apraxia and the supplementary motor area. Archives of Neurology, 43, 787–792. Watson, R. T., & Heilman, K. M. (1983). Callosal apraxia. Brain, 106, 391–403. Zangwill, O. L. (1960). Le Problème de l’apraxie idéatoire. Nerve Neurology, 106, 595–603.

11 Should we make aphasic patients sing? Sylvie Hébert, Isabelle Peretz, and Amélie Racette

Singing is a highly enjoyable experience. It also constitutes the most widespread mode of musical expression. All people across cultures have taken part in singing in some form. This pleasurable experience is most likely rooted in the early exposure to maternal singing, which is swiftly imitated by the infant. Infants spontaneously sing around the age of 1 year. At 18 months, the child begins to generate recognizable, repeatable songs (Ostwald, 1973). These spontaneous songs have a systematic form and display two essential features of adult singing: discrete pitches, and the repetition of rhythmic and melodic contours. They are unlike adult songs, however, because they lack a stable pitch framework (Dowling, 1984). It is later, around the age of 5, that children appear to hold a stable tonality and a regular beat as adults do (Dowling & Harwood, 1986). Thus, by the age of 5, children have a fairly large repertoire of songs of their own culture and display singing abilities that will remain qualitatively unchanged in adulthood, unless the child receives musical tutoring or is regularly practicing in a choir or ensemble. Thus, even without much practice, the ordinary adult seems to be endowed with the basic abilities that are necessary to sing simple songs of their culture. Despite their ubiquity and early acquisition, the singing abilities of aphasic patients and ordinary people in general, are rarely studied. There are two main reasons for this limited attention: cultural bias and measurement problems. First, the widespread cultural bias is that singing is poor in the general population. Most people are believed to be unable to carry a tune. This point of view was probably shared by Luigi Vignolo, who has always been interested in the nonverbal abilities of aphasic patients, as shown by his pioneering work on the recognition of nonverbal sounds (Vignolo, 1969, 1982) and his more recent interest in music processing (Vignolo, 2003). Had Luigi Vignolo trusted his own musical abilities, he would have tried to make his patients sing. Indeed, there is a growing body of research showing that ordinary adults are able to sing. Nonmusicians are found to be highly consistent in their ability to sing familiar songs. They exhibit precise memory for both pitch level and tempo (Halpern, 1988, 1989). This precision in singing seems to hold not only for a given singer, when we measure individual stability across song renditions (Bergeson & Trehub, 2002; Halpern, 1988, 1989), but

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also for a group of singers, when we measure consistency across individuals in the sung recall of a popular song (Levitin, 1994; Levitin & Cook, 1996). Therefore, as far as singing a familiar song is concerned, heterogeneity in singing abilities does not seem to be a serious limitation. The second reason for the neglect of singing abilities relates to the problem of measurement. It is always easier to collect data in the form of responses from a limited set (e.g. “same-different” classification) than it is from multidimensional performance. This concern for precision and simplicity in measurement has led to a concentration of research on musical receptive abilities in the ordinary listener. This is also true in neurological settings. It is unfortunate because production data are much richer. The analysis can rely on auditory transcription into notation, or to auditory-only analysis by expert musicians. For example, Bergeson and Trehub (2002), in their study of maternal singing, had the mothers’ productions judged by two experts, who matched the initial or tonic pitch of the song to a keyboard note, to the nearest quarter tone, and used a metronome to match the average tempo of the renditions. Although constrained by the “ear” of the listeners, to a certain extent, these analyses usually yield very good interrater reliability (95% and over in this case). And more importantly, the examination of production allows discoveries that could not be obtained by simple perception studies. Bergeson and Trehub (2002) found that mothers, when singing to their baby, have little variability in a given song’s starting pitch over 1-week time, whereas they have high variability in their speech starting pitch for a given sentence. This finding suggests that mothers with no special music training have almost an “absolute” mental representation of a song. Although the child’s productions are stable only around the age of 5 years, this remarkably stable rendition of songs by the mother over time may serve different needs in the mother–baby relationship, such as soothing the baby, the promotion of social bonds, and, perhaps, the focusing of attention to particular words of the songs. Some bits of information about the singing of aphasic patients come from neurologists who have commented on, or reported (qualitatively), the singing of their patients. For example, Luria’s famous patient, Zasetsky, was damaged on the left side of the brain. He could easily remember the melodies of songs, though not their words (Luria, 1973). However, many reported that severely aphasic patients who have recovered none or few of their speech abilities are still able to sing previously learned songs with well-articulated and linguistically intelligible words. Such patients, with a very restricted output with respect to spontaneous speech, seem to be able to recover word articulation with the support of melody. These observations come mainly from patients who became aphasic after brain damage due to vascular cerebral accident (Assal, Buttet, & Javet, 1977; Jacome, 1984; Yamadori, Osumi, Masuhara, & Okubo, 1977). For instance, Keith and Aronson (1975) reported the case of a brain-damaged woman who could not express herself by speaking, but could do so by singing phrases such as “How are you?” or “I

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want coffee”. With the exception of Assal et al. (1977), whose patients were amateur or professional musicians, other reports concern patients with no particular music training. Thus, this ability to sing with words seems not to be restricted to people with previous music training, but seems rather to reflect a general trait of cerebral organization. The traditional interpretation of this long-standing observation has been that singing familiar songs depends on right-hemisphere functions, whereas propositional (generative) speech depends on left-hemisphere functions. Damage to the left hemisphere, therefore, would leave intact the patients’ ability to sing previously learned songs, whereas damage to the right hemisphere would impair “automatic” speech and familiar song singing. The question of why aphasic patients would be able to sing while not being able to speak is of clinical and theoretical interest. On a clinical level, the observation of such patients is the origin of the melodic intonation therapy (MIT), a technique that has been considered as the most promising avenue for aphasia rehabilitation by the American Neurology Association (Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology, 1994). MIT does not use the singing of familiar songs per se as a form of therapy. Rather, it uses intonation patterns that exaggerate the normal melodic content of phrases that gradually vary in complexity as the patient makes progress, the underlying idea being that musical tonal ability, a form of singing, is a right-hemisphere function. An early interpretation of successful recovery from aphasia with the MIT technique was that it facilitates the use of language areas of the right hemisphere, after damage to the language areas in the left hemisphere (Albert, Sparks, & Helm, 1973). Subsequently, this interpretation was revised and it was suggested that the increased use of melodic aspects of speech increases the role of the right hemisphere in interhemispheric control of language (Sparks, Helm, & Albert, 1974). However, a study by Belin et al. (1996) did not support either of these interpretations. They examined seven nonfluent aphasic patients who had been successfully treated with MIT after a period of time when spontaneous recovery had stopped. They used PET technology to measure relative cerebral blood flow during the hearing and repetition of untrained words, and during repetition of MIT-loaded words. Repetition of untrained words activated right-hemisphere structures homotopic to those usually involved in language tasks, and deactivated left-hemisphere language-related zones. However, repetition of words trained with MIT elicited the opposite pattern of activation: that is, right-hemisphere structures were deactivated while language-related left-hemisphere structures were active. Thus, activation of language areas homotopic to the damaged ones indicated the persistence of aphasia rather than its recovery, suggesting that right-hemisphere activation is a direct consequence of brain damage rather than an adaptive process. While the study supports the potential value of MIT in functional rehabilitation, this rehabilitation was here associated with a shift from right-hemisphere activation to a reactivation of left-hemisphere structures. This finding is

188 Hébert, Peretz, Racette consistent with other recent data showing reactivation of left-hemisphere structures in successful recovery of language (e.g. Heiss, Kessler, Thiel, Ghaemi, & Karbe, 1999), and contrasts with the classical view about the right-hemisphere structures taking over left-hemisphere structures in aphasia recovery (e.g. Papanicolaou, Moore, Deutsch, Levin, & Eisenberg 1988; Sparks, Helm, & Albert, 1974). Certainly, from a clinical point of view, understanding if, and why, singing may be an important tool in rehabilitation, is of significant importance. On a theoretical level, there is a growing body of evidence supporting the autonomy of speech and music. The terms “aphasia” and “amusia” used in neurology designate acquired impairment of language and music processing, respectively. These disorders occur jointly more often than not (Marin & Perry, 1999), probably because a natural brain lesion or disease is most likely to globally affect cognitive functions such as language and music. However, several clinical cases of patients afflicted with aphasia but without amusia have been described. Often, the patients were professional musicians. The most notable case is probably that of Shebalin, who sustained a second vascular hemorrhage in the left hemisphere of the brain at the age of 57. This stroke left him without speech and deaf to the spoken world. While Shebalin could no longer communicate verbally, he continued to teach and to compose until his death, 4 years later. According to the composer Shostakovitch, one of his peers, Shebalin’s last music was undistinguishable from what he had composed before his illness (Luria, Tsvetkova, & Futer, 1965). Other similar cases have been reported in the literature (Assal, 1973; Basso & Capitani, 1985; Jacome, 1984; Signoret, van Eeckhout, Poncet, & Castaigne, 1987; Tzortzis, Goldblum, Dang, Forette, & Boller, 2000). Aphasia without amusia is, however, not limited to musicians, as illustrated in Zasetsky, who was not musically trained (Luria, 1973). Reverse cases, although less common, have also been reported of the presence of amusia without aphasia. These are more recent cases, and often concern patients who did not have any particular music training. The case of IR, for example, is outstanding, since, despite being able to write poems, IR could not recognize her national anthem or the song “Happy Birthday” (Peretz, Belleville, & Fontaine, 1997). Other such cases have been described (e.g. Ayotte, Peretz, Rousseau, Bard, & Bojanowski, 2000; Griffiths, Rees, Witton, Cross, Shakir, & Green, 1997; Hébert & Peretz, 2001; Peretz et al., 1994; Piccirilli, Sciarma, & Luzzi, 2000; Steinke, Cuddy, & Jakobson, 2001; Wilson & Pressing, 1999). On the whole, such double dissociations suggest independence between language and music processing. Songs, however, probably the most ancient form of art, uniting music and language within the same frame, represent an interesting challenge. Songs are a unique combination of text and music. They are separable in many ways, for they rely on separate codes and are even often composed by different persons. Yet, music and text are linked and are most often, if not always, heard and played in a combined form, from an early age. In normal (healthy)

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listeners, studies have shown that recognition of songs is always better when text and tune are put in their original combination, with respect to when they are heard in a combination other than original. This effect had been taken as evidence that the text and melody of a given song are integrated in memory, which is represented by a single code rather than two (Serafine, Crowder, & Repp, 1984; Serafine, Davidson, Crowder, & Repp, 1986). Further studies, however, have suggested a strong association, rather than integration, between text and melody (Crowder, Serafine, & Repp, 1990; Hébert & Peretz, 2001; Peretz, Radeau, & Arguin, 2004). This strong association in memory would enable music to facilitate word recall. Yet, although music is used as a mnemotechnic to learn and remember text by students and children (Dickson & Grant, 2003), it is still unclear by what mechanisms it would be effective. One hypothesis is that production of words is slowed down when singing compared to when speaking. Kilgour, Jakobson, and Cuddy (2000) have shown that a sung text is better recalled than a spoken text as long as the sung text is slower than the spoken one. When the sung text is compressed to be as brief as the (same) spoken text, the advantage in recall disappears. Speed is thus a crucial variable in the effect of music on word recall. The repetition and simplicity of a melody have also been brought forth as explanations for the better word recall of songs over spoken text: it has been documented that the advantage of having a simple melody repeated throughout a song is reversed when the music is complex and changing (Wallace, 1994). Overall, experimental studies that have addressed the question of the effect of music on verbal recall have mainly examined whether or not presenting music along with text enhances word recall. Only one study has examined whether the response produced (sung or spoken) yields an advantage in word recall according to the way it is presented (sung or spoken). It was found that learning digits by singing on a simple melody rather than merely speaking is detrimental to recall, whether they are presented in a sung or a spoken form, whereas singing has no consequence (either good or bad) on word recall (Jellison & Miller, 1982). We (Racette & Peretz, 2007) recently conducted a study of whether singing is better than speaking in normal listeners, depending on the mode of presentation and production (sung versus spoken). The study was based on oral learning of unfamiliar songs, in three different conditions. In the first condition, the participant listened to the sung version of the lyrics and had to sing them back. This condition will be called the sung-sung condition. In the second condition, the sung-spoken condition, the participant listened to the sung version of the lines and had to recite lyrics, without singing. The comparison of these two conditions aimed at determining the effect of music on production. In the third condition, the divided-spoken condition, the participant listened to the spoken lyrics and recalled only the lyrics. In this condition, presentation was defined as divided because, as the lyrics were spoken, the corresponding melody was sung on /la/ in the background. Consequently, when the lyrics were spoken, the context was equivalent to when lyrics were

190 Hébert, Peretz, Racette sung, since the melody was presented in both cases. Thus, the comparison of the sung-spoken and the divided-spoken conditions aimed to determine the effect of music at encoding. Thirty-six university students participated in our study, half being nonmusicians and half music students. Participants learned one different song in each of the three conditions by an adaptive procedure. Songs selected for the study had eight lines that were taken from real songs composed by a folk singer, but that were unfamiliar to all participants. The percentages of correctly recalled words (all three conditions) and musical notes (sung-sung condition) were calculated. The first surprising finding was that musicians did not recall more words and notes than nonmusicians. This might be explained by the fact that musicians usually learn a song with the score. In the procedure used here, participants had to rely on the auditory code of the song, which is also familiar to nonmusicians. Therefore, musicians had no advantage over nonmusicians in an oral learning procedure with no visual support. When the data of the two groups were pooled, the sung recall was significantly lower than both spoken recalls. This means that music interfered with word recall on production. Moreover, because there were not more words recalled in the sung-spoken condition than in the divided-spoken conditions, there was no facilitation of music at encoding either. The results suggest that the lyrics and melody of a song are represented in independent codes in memory. Participants would have to access both the melody and the lyrics, making singing a dual task, at least in the first steps of learning. To summarize, studies in normal listeners have shown that reduced speed, repetition, and simplicity of music are elements that may help to recall words of songs. Yet, when a sung text is presented as fast as speech, when melodies are complex, when listeners have to produce a sung response, or when text is presented against a melodic background, the advantage of singing over speaking disappears. In other words, a song per se does not grant any actual advantage to text in memory, over text alone. These findings with normal subjects raise questions regarding the classical observation that aphasic patients can sing words that they are unable to pronounce otherwise. In fact, these observations are anecdotal. They were not substantiated by quantitative data of patients’ production. The only study that did so does not support the idea that music facilitates word production. Cohen and Ford (1995) examined the production of 12 patients who became aphasic after a unilateral left-hemisphere vascular accident. Patients were asked to choose three songs from a list of eight songs they had sung in therapy over the previous 3 months. Patients had to produce the words of the choruses of the chosen songs under three experimental conditions, that is, spoken naturally (without any support), spoken with a steady drumbeat accompaniment, and sung accompanied with the melody played on a keyboard. Content, error types, and number of intelligible words per minute were the dependent variables. It was found that the speech content and error types did not differ across conditions, but that word intelligibility was higher

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when utterances were spoken without any support, with respect to when sung or spoken accompanied with a drumbeat. However, several methodological problems weaken the conclusions to be drawn. To name a few, the type and severity of aphasia of the patients were not specified. It is unknown how impaired these patients were in their expressive speech abilities. The group data may not be representative of how each patient performed in the different conditions. For instance, the averaging of performance may create effects that do not reflect any of the individual performance patterns, or may cancel out effects that would have been significant at the individual level (Caramazza & McCloskey, 1988). Moreover, as was suggested by the authors themselves, the word intelligibility index (that is, the average number of intelligible words divided by the average duration of each condition) could have been compromised in the rhythm and melody conditions because judges had to listen to recorded speech with a drumbeat or electric keyboard in the background. Masking effects could thus be involved in the finding of lower intelligibility in these conditions. Another important factor is that the word intelligibility index was only an approximation of the patients’ production, because the whole set of productions was not analyzed. Rather, a random sample taken from each patient in each condition was examined, and this rendered the productions not necessarily comparable from one condition to another, or from one patient to another. Finally, performance on the melody of the songs was not assessed, so it is unknown whether singing with the words was detrimental because patients had to produce both melody and words (a double task), or because the words themselves were more difficult to produce while singing than while reciting with accompaniment. In addition, given that amusia is more often associated with aphasia than not, the presence of amusia, in some, or all of the patients cannot be ruled out: a double deficit (amusia plus aphasia) could, in itself, explain why the singing condition was least successful. We recently revisited this question of singing in expressive aphasia and reported the cases of two aphasic patients in whom we assessed singing and speaking abilities within the same utterances (Hébert, Racette, Gagnon, & Peretz, 2003; Peretz, Gagnon, Hébert, & Macoir, 2004). The first patient, CC, was a severely nonfluent aphasic patient who became aphasic after a stroke. Two experiments examined familiar and novel materials, respectively. CC had to repeat sung words (the sung condition), spoken words (the spoken condition), or melodies on the syllable “la” (the music condition). Productions were analyzed in terms of words and notes produced, in order to establish whether or not music imposes a load on memory and production, as it can occur in text recall. The findings showed that word production was comparable in the sung and the spoken conditions, with both familiar (Figure 11.1) and unfamiliar (Figure 11.2) materials. CC was also as competent as his controls in producing the music, and there was no additional cost to produce the music with the words with respect to the music alone. The same findings were essentially replicated in the second patient, GD,

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Figure 11.1 Percentage of correctly repeated notes or words by CC and his matched controls, with respect to the experimental condition, for familiar songs.

who suffered from primary progressive aphasia. GD was tested on familiar material only since he was too deteriorated at the cognitive level to be tested on novel songs. His production of sung and spoken text was comparable in terms of number of syllables correctly repeated. His production of notes was significantly higher than for text, and comparable in the sung and music conditions. Also, in both cases, the same error types were found on spoken and sung words (Figure 11.3). These two patients, having word-finding difficulties from different causes, point to the idea of separate codes for language and music in songs, rather than to granting songs a special status in the cognitive auditory system. The fact that nonfluent aphasic patients are able to sing, as reported previously, could therefore stem from the mere observation that their rote memory of automatic material, such as songs, is superior to their performance in generative tasks, such as spontaneous speech. This was indeed the case for CC and GD. In another study (Racette, Bard, & Peretz, 2006), we examined the

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Figure 11.2 Percentage of correctly repeated notes or words by CC and his matched controls, with respect to the experimental condition, for unfamiliar songs.

production of sung and spoken words of aphasic patients following the same paradigm as the one described earlier in normal listeners, and that involved the production of sung or spoken words in three conditions (sung-sung, spoken-sung, and divided-spoken). Eight patients suffering from a variety of expressive aphasia (going from anomia to severe mixed aphasia) after a leftsided brain lesion were tested. There was no difference between conditions. Thus, singing did not improve word production compared to speaking. This was true for the quantity of words produced but also for the types of errors in the different conditions. Moreover, aphasic patients did not produce more words than notes. The same profile was obtained in subsequent experiments using familiar material. Hence, there were as few words of familiar songs repeated by singing or by speaking. Even if songs were naturally sung with both the lyrics and the melody, there was no cost of producing the lyrics alone. This again suggests that the words and the melody are accessed separately in memory for songs.

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Figure 11.3 Percentage of correctly repeated syllables with respect to the experimental condition for GD.

Would these findings constitute grounds for discontinuing the use of MIT in speech therapy or music therapy sessions? We would like to argue quite the opposite. First of all, the fact that empirical studies point to independence between language and music suggests that the transfer of skills acquired from singing to speaking has real potential to occur. The suggestion of a special right-hemisphere competence for singing with words, which would involve mechanisms different than for speaking, would represent a serious clinical obstruction to therapeutic success. For instance, if patients had to learn words in songs in therapy, they would then have to learn not to sing those words for a transfer from singing to speaking to occur in their daily life. This type of rehabilitation would not constitute a very sensible strategy. The suggestion of special mechanisms for singing words and speaking would also stand in contrast with the increasingly growing (empirical and brain imaging) evidence on the independence of language and music neural networks. Secondly, studies did show that presentation of a sung text, in a natural context (that is, when songs are not artificially compressed for faster presentation) and with normal (simple and repetitive) melodies, is superior to a spoken text on recall, or at least is not detrimental to it. For instance, syllable lengthening, which is an acoustic correlate of speed reduction in singing, helps nonfluent aphasic patients when they use MIT; the longer the syllables are, the more phrases are produced by patients (Laughlin, Naeser, & Gordon, 1979). Singing generally enhances fluency and word intelligibility of patients with speech disorders such as dysarthria or stuttering, possibly or partly

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via such mechanisms, although rigorous empirical studies are still lacking (Cohen, 1988; Colcord & Adams, 1979; Healey, Mallard, & Adams, 1976; Pilon, McIntosh, & Thaut, 1998). Studies using language pathologies other than aphasia are crucially needed. In particular, one common characteristic of the patients examined in our studies is that they all had word-finding difficulties. The advantages of singing over speaking could well be more apparent in other language disorders involving suprasegmental (beyond the word) impediments. For instance, we (Hébert & Béland, unpublished data) examined the case of a stutterer and compared his fluency during sung, spoken, and spoken-pacedwith-a-metronome renditions of the same texts. While, in terms of percentage of words, the advantage of sung words over spoken was modest (but nevertheless significant, in the order of about 5% and 15% for familiar and unfamiliar songs, respectively), it was when listening to his productions that the difference between these conditions was astonishing. The improvement could not be explained by speed reduction, since word production was faster when the patient spoke to the pulse of a metronome (therefore, it was not singing per se), and the performance in the latter condition was comparable to when singing. Thus, although improvement did occur when singing, the singing per se did not give this advantage, since metronome-paced speech was as good as singing. However, maybe some component (yet to be found) that encompasses the word level, and that is common to singing and metronomepaced speech, is responsible for these effects. Another study (Kempler & Van Lancker, 2002) examined the intelligibility in a dysarthric patient with Parkinson’s disease in spontaneous speech, reading aloud, repetition, repeated singing, and spontaneous singing. The singing stimuli (both repeated and spontaneous) were conversational phrases such as “It’s a small village”, similar to what is used in MIT. Not surprisingly, the spontaneous speech was found less intelligible than the other conditions, which did not differ significantly from each other. However, an interesting finding was that spontaneous singing was louder than the other conditions. Dysfluencies were also more frequent in spontaneous speech than in the other conditions. Disturbance in speech rate and reduced speech volume have been described as a prominent and even as an initial clinical feature of Parkinson’s disease. Speech impairments in this disease also include imprecise articulation, prosodic abnormalities, monotone, reduced stress, monoloudness, imprecise consonants, inappropriate silences, short rushes, harsh voice, continuous breathiness, pitch level disturbances, and variable rate, to name but a few. Therefore, even if in terms of number of words singing has no advantage over speaking, the communication benefits that could be gained with music in therapy (via MIT or active music therapy) for this population are hardly doubtful. And this is exactly what Pacchetti, Mancini, Aglieri, Fundarò, Martignoni, and Nappi (2000) have shown. They compared physical therapy sessions (which included passive stretching, specific motor tasks, and strategies to improve balance and gait) with active music therapy sessions (which

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included choral singing, voice exercise, rhythmic and free body movements, and active music involving collective invention). While physical therapy produced significant improvement over music therapy in rigidity, music therapy produced significant improvement in bradykinesia (at a motor level), as well as in happiness, activities of daily living, and quality of life, over physical therapy. These studies bring about two further points: the fluency issue and additional benefits from speech and music therapy. Fluency is an ill-defined concept that is difficult to measure empirically, and its corresponding acoustic cues are unknown (Gordon, 1998). Rather, what we are aware of are fluency disruptions. Although fluency can be thought as applying to the word level (as in stuttering, for instance), it is most useful to describe prosody or phrase contour (that is, beyond the word level). In our studies reported here (aphasic and stuttered patients), the singing conditions yielded a strong impression of fluency that was not captured by the number of words or syllables produced. Therefore, the impression of fluency in singing, presumably produced by the smooth legato between words (i.e., no or few pauses), certainly contrasts with the limited and jerky spontaneous speech of nonfluent aphasic patients, stutterers, and possibly patients with Parkinson’s disease. A therapy based on the exaggeration of prosody, perhaps by singing, may provide grounds for better modeling of sentence production. Finally, additional benefits may be provided by music in therapy. First, because aphasic patients do not necessarily suffer from a music disorder (Hébert et al., 2003; Peretz et al., 2004), producing musical notes alone is still a good way for them to produce vocal sounds, and incidentally develop proper breathing and increase in volume. Second, a treatment emphasizing the rhythmic support of speech may improve repetition to a greater extent than the melodic support (Boucher, Garcia, Fleurant, & Paradis, 2001). Finally, most aphasic patients seem to enjoy singing, which motivates them to participate in sessions and keeps their spirits high. Music and language have to be compared on similar levels to determine whether they share or not the same underlying processes. When comparing the production of sung and spoken words, it was suggested that there is a unique speech code for words, be they sung or spoken. This verbal code would be separated from the musical code for musical notes production. Therefore, oral production of words and music in neurologically intact participants and in aphasic patients gave additional support for independent representations of music and language in memory for songs. However, the extent of interinfluence between music and language in songs, and how one can benefit from the presence of the other when damaged, because of the strong association between the two, has to be studied further.

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Acknowledgments The writing of this chapter was made possible by a grant from Natural Sciences and Engineering Research Council of Canada (NSERC) to both S.H. and I.P.; by a grant from the International Human Frontier Science Program to I.P. and A.R.; and by a Canadian Institutes for Health Research (CIHR) graduate fellowship to A.R.

References Albert, M. L., Sparks, R. W., & Helm, N. A. (1973). Melodic intonation therapy for aphasia. Archives of Neurology, 29, 130–131. Assal, G. (1973). Wernicke’s aphasia without amusia in a pianist. Revue Neurologique, 129, 251–255. Assal, G., Buttet, J., & Javet, R. C. (1977). Aptitudes musicales chez les aphasiques. Revue Medical Suisse Romande, 97, 5–12. Ayotte, J., Peretz, I., Rousseau, I., Bard, C., & Bojanowski, M. (2000). Patterns of music agnosia associated with middle cerebral artery infarcts. Brain, 123, 1926–1938. Basso, A., & Capitani, E. (1985). Spared musical abilities in a conductor with global aphasia and ideomotor apraxia. Journal of Neurology, Neurosurgery, and Psychiatry, 48, 407–412. Belin, P., Van Eeckhout, P., Zilbovicius, M., Remy, P., François, C., Guillaume, S., et al. (1996). Recovery from nonfluent aphasia after melodic intonation therapy: A PET study. Neurology, 47, 1504–1511. Bergeson, T. R., & Trehub, S. E. (2002). Absolute pitch and tempo in mother’s songs to infants. Psychological Science, 13, 72–75. Boucher, V., Garcia, L. J., Fleurant, J., & Paradis, J. (2001). Variable efficacy of rhythm and tone in melody-based interventions: Implications for the assumption of a right-hemisphere facilitation in non-fluent aphasia. Aphasiology, 15, 131–149. Cadalbert, A., Landis, T., Regard, M., & Graves, R. E. (1994). Singing with and without words: Hemispheric asymmetries in motor control. Journal of Clinical and Experimental Neuropsychology, 16, 664–670. Caramazza, A., & McCloskey, M. (1988). The case for single-patient studies. Cognitive Neuropsychology, 5, 517–527. Cohen, N. S. (1988). The use of superimposed rhythm to decrease the rate of speech in a brain-damaged adolescent. Journal of Music Therapy, 25, 85–93. Cohen, N. S., & Ford, J. (1995). The effects of musical cues on the nonpurposive speech of persons with aphasia. Journal of Music Therapy, 32, 46–57. Colcord, R. D., & Adams, M. R. (1979). Voicing duration and vocal SPL changes associated with stuttering reduction during singing. Journal of Speech, Language, and Hearing Research, 22, 468–479. Crowder, R. G., Serafine, M. L., & Repp, B. (1990). Physical interaction and association by contiguity in memory for the words and melodies of songs. Memory and Cognition, 18, 469–476. Dickson, D., & Grant, L. (2003). Physics karaoke: Why not? Physics Education, 38, 320–323. Dowling, W. J. (1984). Development of musical schemata in children’s spontaneous

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singing. In W. R. Crozier & A. J. Chapman (Eds.), Cognitive processes in the perception of art (pp. 145–163). Amsterdam: North-Holland. Dowling, W. J., & Harwood, D. (1986). Music cognition. New York: Academic Press. Epstein, C. M., Meador, K. J., Loring, D. W., Wright, R. J., Weissman, J. D., Sheppard, S., et al. (1999). Localization and characterization of speech arrest during transcranial magnetic stimulation. Clinical Neurophysiology, 110, 1073–1079. Gordon, J. K. (1998). The fluency dimension in aphasia. Aphasiology, 12, 673–688. Griffiths, T. D., Rees, A., Witton, C., Cross, P. M., Shakir, R. A., & Green, G. G. (1997). Spatial and temporal auditory processing deficits following right hemisphere infarction. A psychophysical study. Brain, 120, 785–794. Halpern, A. R. (1988). Perceived and imagined tempos of familiar songs. Music Perception, 6, 193–202. Halpern, A. R. (1989). Memory for the absolute pitch of familiar songs. Memory and Cognition, 17, 572–581. Healey, E. C., Mallard, A. R. III, & Adams, M. R. (1976). Factors contributing to the reduction of stuttering during singing. Journal of Speech, Language, and Hearing Research, 19, 475–480. Hébert, S., & Peretz, I. (2001). Are text and tune of familiar songs separable by brain damage? Brain and Cognition, 46, 169–175. Hébert, S., Racette, A., Gagnon, L., & Peretz, I. (2003). Revisiting the dissociation between singing and speaking in expressive aphasia. Brain, 126, 1836–1850. Heiss, W. D., Kessler, J., Thiel, A., Ghaemi, M., & Karbe, H. (1999). Differential capacity of left and right hemispheric areas for compensation of poststroke aphasia. Annals of Neurology, 45, 430–438. Jacome, D. E. (1984). Aphasia with elation, hypermusia, musicophilia and compulsive whistling. Journal of Neurology, Neurosurgery, and Psychiatry, 47, 308–310. Jellison, J. A., & Miller, N. L. (1982). Recall of digit and word sequences by musicians and nonmusicians as a function of spoken or sung input and task. Journal of Music Therapy, 19, 194–209. Keith, R. L., & Aronson, A. E. (1975). Singing as therapy for apraxia of speech and aphasia: Report of a case. Brain and Language, 2, 483–488. Kempler, D., & Van Lancker, D. (2002). Effect of speech task on intelligibility in dysarthria: A case study of Parkinson’s disease. Brain and Language, 80, 449–464. Kilgour, A. R., Jakobson, L. S., & Cuddy, L. L. (2000). Music training and rate of presentation as mediators of text and song recall. Memory and Cognition, 28, 700–710. Laughlin, S. A., Naeser, M. A., & Gordon, W. P. (1979). Effects of three syllable durations using the melodic intonation therapy technique. Journal of Speech, Language, and Hearing Research, 22, 311–320. Levitin, D. J. (1994). Absolute memory for musical pitch: Evidence from the production of learned melodies. Perception and Psychophysics, 56, 414–423. Levitin, D. J., & Cook, P. R. (1996). Memory for musical tempo: Additional evidence that auditory memory is absolute. Perception and Psychophysics, 58, 927–935. Luria, A. R. (1973). The man with a shattered world (pp. 154–155) (L. Solotaroff, Trans.). London: Cape. Luria, A. R., Tsvetkova, L. S., & Futer, D. S. (1965). Aphasia in a composer (V. G. Shebalin). Journal of Neurological Sciences, 2, 288–292. Marin, O. S., & Perry, D. W. (1999). Neurological aspects of music perception and

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performance. In D. Deutsch (Ed.), The psychology of music (2nd ed., pp. 653–724). New York: Academic Press. Ostwald, P. F. (1973). Musical behavior in early childhood. Developmental Medicine and Child Neurology, 15, 367–375. Pacchetti, C., Mancini, F., Aglieri, R., Fundarò, C., Martignoni, E., & Nappi, G. (2000). Active music therapy in Parkinson’s disease: An integrative method for motor and emotional rehabilitation. Psychosomatic Medicine, 62, 386–393. Papanicolaou, A. C., Moore, B. D., Deutsch, G., Levin, H. S., & Eisenberg, H. M. (1988). Evidence for right-hemisphere involvement in recovery from aphasia. Archives of Neurology, 45, 1025–1029. Peretz, I., Belleville, S., & Fontaine, F. (1997). Dissociations entre musique et langage après atteinte cérébrale: Un nouveau cas d’amusie sans aphasie. Canadian Journal of Experimental Psychology, 51, 354–367. Peretz, I., Gagnon, L., Hébert, S., & Macoir, J. (2004). Singing in the brain: Insights from cognitive neuropsychology. Music Perception, 21, 373–390. Peretz, I., Kolinsky, R., Tramo, M., Labrecque, R., Hublet, C., Demeurisse, G., et al. (1994). Functional dissociations following bilateral lesions of auditory cortex. Brain, 117, 1283–1302. Peretz, I., Radeau, M., & Arguin, M. (2004). Two-way interactions between music and language: Evidence from priming recognition of tune and lyrics in familiar songs. Memory and Cognition, 32, 142–152. Piccirilli, M., Sciarma, T., & Luzzi, S. (2000). Modularity of music: Evidence from a case of pure amusia. Journal of Neurology, Neurosurgery, and Psychiatry, 69, 541–545. Pilon, M. A., McIntosh, K. W., & Thaut, M. H. (1998). Auditory vs. visual speech timing cues as external rate control to enhance verbal intelligibility in mixed spastic-ataxic dysarthric speakers: A pilot study. Brain Injury, 12, 793–803. Racette, A., Bard, C., & Peretz, I. (2006). Making non-fluent aphasics speak: Sing along! Brain, 129, 2571–2584. Racette, A., & Peretz, I. (2007). Learning lyrics: To sing or not to sing? Memory and Cognition, 35, 242–253. Rubin, D. C. (1977). Very long-term memory for prose and verse. Journal of Verbal Learning and Verbal Behavior, 16, 611–621. Ryding, E., Bradvik, B., & Ingvar, D. H. (1987). Changes of regional cerebral blood flow measured simultaneously in the right and left hemisphere during automatic speech and humming. Brain, 110, 1345–1358. Serafine, M. L., Crowder, R. G., & Repp, B. H. (1984). Integration of melody and text in memory for songs. Cognition, 16, 285–303. Serafine, M. L., Davidson, J., Crowder, R. G., & Repp, B. H. (1986). On the nature of melody–text integration in memory for songs. Journal of Memory and Language, 25, 123–135. Signoret, J. L., van Eeckhout, P., Poncet, M., & Castaigne, P. (1987). Aphasia without amusia in a blind organist: Verbal alexia-agraphia without Braille. Revue Neurologique, 143, 172–181. Sparks, R., Helm, N., & Albert, M. (1974). Aphasia rehabilitation resulting from melodic intonation therapy. Cortex, 10, 303–316. Steinke, W. R., Cuddy, L. L., & Jakobson, L. S. (2001). Dissociations among functional subsystems governing melody recognition after right hemisphere damage. Cognitive Neuropsychology, 18, 411–437.

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Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (1994). Assessment: Melodic intonation therapy. Report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology. Neurology, 44, 566–568. Tzortzis, C., Goldblum, M. C., Dang, M., Forette, F., & Boller, F. (2000). Absence of amusia and preserved naming of musical instruments in an aphasic composer. Cortex, 36, 227–242. Vignolo, L. A. (1969). Auditory agnosia: A review and report of recent evidence. In A. L. Benton (Ed.), Contributions to clinical neuropsychology (pp. 172–208). Chicago: Aldine. Vignolo, L. A. (1982). Auditory agnosia. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 298(1089), 49–57. Vignolo, L. A. (2003). Music agnosia and auditory agnosia. Dissociations in stroke patients. Annals of the New York Academy of Sciences, 999, 50–57. Wallace, W. T. (1994). Memory for music: Effect of melody on recall of text. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 1471–1485. Wilson, S. J., & Pressing, J. (1999). Neuropsychological assessment and the modeling of musical deficits. In R. R. Pratt & D. Erdonmez Grocke (Eds.), Music medicine and music therapy: Expanding horizons (pp. 47–74). Melbourne: University of Melbourne Press. Yamadori, A., Osumi, Y., Masuhara, S., & Okubo, M. (1977). Preservation of singing in Broca’s aphasia. Journal of Neurology, Neurosurgery, and Psychiatry, 40, 221–224.

12 The neuropsychology of calculation and number processing Xavier Seron

It is not easy for a numerate person to understand the everyday consequences of acquired calculation and number deficits. However, we need numbers in many daily activities: to have a sense of time, to locate a house, to change money, to understand the score of a match, to read a price, to estimate a distance, to make a telephone call, and so on. Not only do we have to understand numbers, but we also have to be able to manipulate them for cooking, driving a car, changing money, selling, buying, checking our bank account, arriving in time for an appointment, and so on. Although the domain of number is crucial in everyday situations, it has been neglected for a very long time in neuropsychology, and it is only over the last 20 years that the neuropsychological approaches to numbers and calculation have made any major progress. Although debate still rages over the cognitive architecture of our numerical abilities, a great deal of research has delineated the main questions that remain to be solved. In our review of the domain, I will arbitrarily consider two main fields: the basic quantification processes and the numerical and arithmetic symbolic processes. At the end of the chapter, I will also discuss some aspects of the relationships between symbolic and non-symbolic arithmetic. There is a consensus within scientific literature that before the acquisition of symbolic arithmetic, human babies, as well as several animal species, possess some mechanisms to discriminate, categorize, and represent the numerosities of objects or events (Hauser, Carey, & Hauser, 2000). It has indeed been observed that babies and young children, well before the appearance of language, react specifically to changes in numerosities, and that such a capacity for discrimination operates in a precise way in the range of small numbers (up to 3 and sometimes 4), but becomes approximate for larger numerosities (Antell & Keating, 1983; Starkey & Cooper, 1980; Strauss & Curtis, 1981). It has also been shown that children as young as 4½ months can anticipate the results of simple addition and subtraction (Wynn, 1992). However, many debates continue on (1) the philogenic continuity between human and animal numerical competencies, (2) the format of these “protonumeric” representations, and (3) the relationships between these precocious protonumeric mechanisms and the subsequent adult arithmetic competencies. Some authors

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suggest that there is a direct link between the initial numerical competencies and the symbolic adult competencies (Butterworth, 1999; Dehaene, 1997), while others consider that the appearance of language creates a gap, a discontinuity, in the development (Carey, 2001). In this review, I will examine the contribution of neuropsychology to some of these debates by looking first at some basic numerical competencies, and then by examining numerical and arithmetical activities that require the use of language and of symbolic arithmetic such as transcoding processes and simple calculation. Finally, in the last section, I will discuss the question of the semantic representation of numbers.

Basic quantification processes As concerns our basic quantification abilities, three mechanisms have been described: subitizing, counting, and estimation. Subitizing is a nearly instantaneous process that allows us to discriminate between small sets of different sizes (up to three). Subitizing occurs automatically, accurately, and without conscious attention. At the chronometric level, subitizing is characterized by a very modest increase in the reaction times according to the number of elements to be estimated (no more that 50 ms per item), while for more than three items, the reaction times abruptly increases by up to 200 ms per item. This increase in response time is considered to reflect the intervention of a counting process. Counting is a more complex process that requires an association between the elements to be counted and the sequence of verbal numerals according to some basic counting principles (Gallistel & Gelman, 1982). Finally, for the numerosities above the subitizing range, when counting is not possible (because the stimuli are presented too briefly or are too numerous, for example), the numerosity of the sets can nevertheless be evaluated through the use of an estimation process that gives only an approximate representation of the size of the set. Some unsolved questions remain about these three quantification processes. A first question is whether subitizing and counting are actually different mechanisms, or whether the difference is limited to the degree of difficulty. Some data from experimental psychology indicate that, on the one hand, counting, unlike subitizing, is influenced by different experimental manipulations related to the control of ocular movements, the spatial organization of the items, the load in short-term memory, the homogeneity of the stimuli, or the cueing of attention (Piazza, 2004). On the other hand, the only variable that influences subitizing but not counting is the manipulation of the saliency of the targets (the perceptive pop-out). Such an asymmetry in the variables that specifically influence the two processes may nevertheless be interpreted by considering that subitizing is in fact a rapid and automated counting process that can be affected only by a reduction in the perceptive pop-out. Furthermore, the critical discontinuity in the reaction times around the limit of four stimuli, which is considered as the frontier between the two processes,

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has not always been observed, and its statistical reliability is questioned (Balakrishman & Ashby, 1992). The issue is thus uncertain, and it is interesting to examine whether there is any evidence in neuropsychology for a dissociation between these two abilities. Dehaene and Cohen (1994) have documented a dissociation between a preserved ability to subitize small collections of objects and impaired counting abilities through the individual analysis of five patients presenting a simultagnosia. The patients were given quantification tasks ranging from one to six items in random or canonical presentation, both accuracy and response time measures being used. They proved to be able to subitize two or (less often) three objects, while their counting performance beyond this range was clearly impaired. However, the French authors have examined the visual exploration of their patients and have shown in a classical conjunction research task that their visual exploration was slower than that of normal subjects. Thus, they proposed that the impaired counting performance in simultagnosic patients is due to a fundamental inability to use spatial tags to keep track of previously explored locations. In this view, subitizing was preserved because it depends on a preserved parallel searching algorithm different from the serial research processing typically involved in counting, and that is impaired in simultagnosic patients. Such observations, however, constitute a pattern of simple dissociation that may simply mean that the impaired task is more complex than the preserved one. Given that it is legitimate to postulate that the quantification process becomes more difficult with the increase in numerosities, the preservation of subitizing together with a deficit in counting is not theoretically constraining. A more convincing proof would be to observe patients unable to subitize but still able to count objects. Two such patients have been described in the literature, but neither is convincing. The first patient, exhibiting a developmental dyscalculia, Charles, has been described by Butterworth (1999). The patient was able to estimate the elements of a collection only if he received enough time to count them. Furthermore, when asked to evaluate dots in the range of subitizing, Charles showed an increase in his reaction times of about 200 ms for the dots, suggesting that he used a counting strategy. However, recent data have demonstrated that he was still able to estimate small numerosities even for a very brief stimuli presentation (100 ms) and that he presented the classical discontinuity around the numerosity four (Piazza, 2004). A second patient, described by Cipolotti, Butterworth, and Denes (1991), was a woman with Gerstmann syndrome with very severe acalculia. She was unable to correctly subitize a set of dots arranged in the canonical way, but could count aloud and point out the dots (Cipolotti et al., 1991). However, the fact that this woman was unable to process any numerosity or number beyond four cannot be considered as a strong argument for the dissociation of the two mechanisms since she was only able to count within the subitizing range. Research on counting is limited in neuropsychology. Deficits in counting have, however, been observed in different groups of patients: simultagnosic patients (Cohen & Dehaene, 1995), those with right and left hemisphere

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lesions (Seron, Deloche, & Cornet, 1991; Warrington & James, 1967), and those with dementia (Halpern, McMillan, Moore, Dennis, & Grossman, 2003; Seron et al., 1991). With regard to demented patients, it has been shown that frontotemporal dementia (FTD) and dementia of Alzheimer type (DAT) patients score better than those with corticobasal degeneration (CBD). However, most of these studies concerned the counting of small numerosities, and the only study devoted to large dot arrays has been done by Seron and his collaborators on a group of aphasic, right-brain-damaged, and demented subjects. The results indicated that right-brain-damaged subjects encountered more difficulty with the spatial components of the task (correctly pointing to the dots), while aphasics experienced more difficulty with its verbal components (producing the correct number word sequence). The difficulties evidenced by demented patients were less systematic. Finally, the detailed analysis of the patients’ strategies indicated that the basic counting principles (cardinality, one-to-one correspondence, and the word-order principle) proposed by Gallistel and Gelman (1992) and Fuson (1988) were preserved, but that the patients had some difficulty with their correct application. This result is interesting but concerns only a small sample of demented subjects (seven patients). However, preservation of a good level of performance in dot counting as well as in subitizing has been observed in a subsequent study with a more extended sample of demented subjects (Kaufmann, Montanes, Jacquier, Matallana, Eibl, & Delazer, 2002). Approximate estimation of large numerosities without resorting to counting has not been systematically studied in neuropsychology. Some research has been done on the estimation of numerosities in specific contexts, but these studies do not tap into the basic estimation quantification process. As we can see, up to now, the basic quantification processes have not been systematically studied by neuropsychologists. Furthermore, most studies are limited insofar as they have mixed basic quantification processes and symbolic arithmetic. In most studies, indeed, the subjects have been asked to give their answer orally. Thus, there is a lack of studies looking into basic numeric and arithmetical skills that do not require a symbolic component. However, even if there is a lack of sufficient data, the present results suggest that the basic quantification processes are more resistant to brain damage than symbolic arithmetic (Girelli & Delazer, 2001).

Symbolic arithmetic In symbolic arithmetic, the research has been more extensive and can be grouped into two main domains: the processing of numerals (writing, reading, and transcoding) and basic calculation. We will briefly examine what has been observed and the main unsolved questions.

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Processing of numerals One of the particularities of the numerical domain is the presence in the written modality of two different notation systems: Arabic and verbal numerals. These two notation systems are composed of different elements and present a different structure. The Arabic system is a logographic one, since its smallest units (the digits) represent a quantity, whereas the verbal system is alphabetic. Its smallest units (the letters) have no meaning but represent the sound of the language. Both systems are, however, equally able to represent with precision an infinity of numerosities, and any quantity may be expressed without ambiguity in both notations.1 The verbal system does not permit easy calculation, unlike the Arabic system that sustains most of our complex written calculations. In the initial research on acalculia, it was observed that some patients essentially presented difficulties in reading or writing Arabic numerals (Hécaen, Angerlergues, & Houiller, 1961; Henschen, 1926). But in these group studies, the description of the disorders was relatively vague, and while in the rare, old single-case studies the descriptions were more refined, the authors did not propose any interpretation of the disorders (Benson & Denckla, 1969; Berger, 1926; Lewandowsky & Stadelman, 1908; Singer & Low, 1933). A first question concerns the existence of a specific lexical component for Arabic numerals. Some authors have proposed that Arabic digits are processed like objects and contact their semantic representation directly (Brysbaert, 2005). By comparison with words, Arabic numerals indeed lack many of the classical characteristics of language lexical entities. They do not have morphological, phonological, or orthographic information, and they do not play any syntactic role. However, unlike objects, they enter into sequential compositions following precise rules in order to constitute an infinity of numerosities. However, even if many authors postulate that there is an Arabic lexicon, it remains difficult to establish its content and its precise extension. Aside from the Arabic lexical primitives, such a lexicon may well contain frequently used Arabic numerals such as some round numbers (10, 100, 500) and maybe also all the two-digit numbers. The Arabic lexicon may also contain familiar Arabic numerals corresponding to encyclopaedic knowledge (such as certain historical dates, ages, brands of cars, etc.). A better reading of familiar numerals (such as 1789, the date of the French Revolution) than unfamiliar ones (such as 8179) has indeed been shown in single-case studies (Cohen, Dehaene, & Verstichel, 1994; Delazer & Girelli, 1997). Most of the research on the processing of numerals has been done under the heading of the transcoding processes. Transcoding refers to the processes involved in the transformation of numerals presented in a specific notation system or modality into another one. One can distinguish between intranotation transcodings, as in reading written verbal numerals aloud, and internotation transcodings, when this results in a change of notation, such as reading Arabic numerals aloud or writing Arabic numerals under

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dictation. The first detailed studies on transcoding were performed by Deloche and Seron (Deloche & Seron, 1982a, 1982b; Seron & Deloche, 1983, 1984), who observed two types of transcoding errors: the lexical errors resulting in lexical substitutions or omissions (twenty-four → 23) and syntactic errors that result in a transformation of the whole structure of the numerals (twenty thousand one hundred and forty → 2,010,010,040). Similar dissociations between lexical and syntactical errors have since been reported frequently in the literature (Cipolotti, Butterworth, & Warrington, 1994; Delazer & Denes, 1998; McCloskey, Caramazza, & Basili, 1985; McCloskey, Sokol, & Goodman, 1986; Noël & Seron, 1993, 1995). Other dissociations between impaired and preserved components in transcoding have been observed between comprehension and production mechanisms, and between the two notation systems. Patients have been described with preserved comprehension mechanisms, together with impaired production mechanisms, while the reverse performance profile has also been reported (Benson & Denckla, 1969; McCloskey, Sokol, & Goodman, 1986; Singer & Low, 1933). Similarly, dissociations between notation systems have been observed, such as impaired comprehension of verbal numerals with intact understanding of Arabic numerals (McCloskey & Caramazza, 1987; McCloskey et al., 1985, 1986) and vice versa (preserved understanding of verbal numerals together with impaired comprehension of Arabic numerals) (Delazer & Girelli, 2004; McCloskey et al., 1985). Finally, dissociations between notations have also been described at the production level in a patient able to produce Arabic numerals while presenting an impaired production of verbal numerals (McCloskey, Sokol, Goodman-Shuman, & Caramazza, 1990). These observations have generally been interpreted as the result of selective breakdowns within a modular functional architecture proposed by McCloskey and Caramazza (McCloskey & Caramazza, 1987; McCloskey et al., 1985, 1986). McCloskey’s model for number and calculation processing is a classical modular architecture that presents many similarities (but also some noticeable differences from) to the functional architectures proposed in the 1970s for reading, writing, and other lexical processes. The architecture is composed of comprehension and production modules for the Arabic and verbal formats. The comprehension modules are used to generate a semantic representation of the number; that is, a representation of the quantity to which the number refers. The production modules convert the semantic representation of a number into the appropriate output format (Arabic or verbal). Mental calculation and other arithmetical processes are performed in specific modules on amodal abstract representations resulting from encoding stages. This architecture had provided a general framework that allows the interpretation of most of the double dissociations observed between lexical and syntactic mechanisms, between verbal and Arabic numerals, and between comprehension and production mechanisms. However, immediately after its publication, McCloskey’s architecture was questioned on several points. The two major criticisms concerned (1) the existence of a central semantic

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representation that constitutes an obligatory bottleneck between the satellite input and output systems, and (2) the format of the semantic representation of numbers (Campbell & Clark, 1988, 1992). We will briefly examine these two continuing debates. McCloskey’s model, assumes that transcodings are achieved by the successive activation of the comprehension, production, and semantic modules. For instance, reading aloud an Arabic numeral such as “345” requires the intervention of the Arabic comprehension module in order to recognize the lexical Arabic primitives, to analyse their position in the sequence, and to transform it into the corresponding base-10 semantic representation (here: {3}10EXP2; {4}10EXP1; {5}10EXP0). Then the verbal production module translates this semantic representation into the verbal numeral “three hundred and fortyfive”. In this perspective, the base-10 semantic representation of numbers constitutes an obligatory bottleneck between the input and output systems for transcoding operations. A direct consequence of the model is that if subjects can transcode a numeral, they can also understand the quantity it represents. In contrast to this semantic transcoding model, alternative models that do not require an intermediary elaboration of a semantic value of the number between the input and the output numerals have been proposed (e.g. Cipolotti & Butterworth, 1995; Dehaene, 1992; Deloche & Seron, 1982a, 1982b; Seron & Deloche, 1983, 1984). In the asemantic models, the output numeral is simply produced by applying a set of rewriting rules to the lexical primitives of the input numeral. In reference to the dual-route models for word reading, it has also been suggested that both conceptions are valid and that there may be parallel semantic and asemantic routes for numeral transcoding (Cipolotti, 1995). However, the demonstration of the existence of two different types of transcoding is not that simple to establish. At first view, and by analogy with word reading, the existence of two transcoding routes may require (1) patients able to transcode Arabic numerals into verbal numerals without being able to understand them, and symmetrically (2) patients able to transcode Arabic numerals into verbal numerals by a semantic route, but unable to transcode them by the non-semantic route (Seron & Noël, 1995). Yet, if there are two routes and if one is impaired, then it is expected that the other may compensate. However, as concerns Arabic numerals, it is difficult to establish which route is used because routes have no specific signature. There is indeed an important difference between word reading and reading of Arabic numerals. In word reading, when the lexical route is impaired, the functioning of the asemantic route is revealed by the appearance of specific regularization errors in the reading of irregular words. Symmetrically, when the impairment concerns the asemantic route, this is suggested by the patient’s incapacity to read non-words or unfamiliar words. At first sight, a similar line of reasoning might apply to the reading of Arabic numerals. However, any attempt to prove such a double dissociation faces two particular difficulties. First, every Arabic sequence can, in principle, be transcoded via a non-lexical route because there are no “irregular numerals” (except

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maybe those beginning with zero). Consequently, if the semantic route is damaged, the non-lexical route would in principle be able to read every numeral. Second, every unfamiliar numeral may in principle receive an interpretation via a semantic route, since it is always possible to compute its corresponding meaning or numerical value. Therefore, in case of lesion of the non-lexical route, the semantic route may still mediate the reading of every numeral. The evidence for a dual-route reading process is thus more complex to establish in the domain of Arabic numerals than in the case of word reading. Nevertheless, many single-case studies that are not compatible with McCloskey’s semantic model have been published. Firstly, it has been observed in transcoding tasks that the pattern of errors produced by some patients is more easily interpreted by the use of asemantic mechanisms acting directly on the entry codes than by the use of a semantic algorithm. For example, the patient LR described by Noël and Seron (1995), while correctly understanding the verbal numerals, made different types of errors when he had to transcode two different verbal numerals sharing in McCloskey’s model the same semantic representation such as “one thousand and five hundred” or “fifteen hundred”. Although LR understood these two numerals well, he made different errors: “1,000,500” for “one thousand and five hundred” and “1500” for “fifteen hundred”. This pattern of errors suggests that for LR the production of Arabic numerals is not guided by a base-10 abstract semantic representation, but, rather, it is the syntactic structure of the verbal numerals that influences the production of the corresponding Arabic numerals. In the same way, the observation of specific errors made by the French aphasics on complex teens, such as transcoding “quatre-vingt dix sept” as “420,107,”2 seems to suggest that the errors are due to impaired mechanisms acting upon the elements of the verbal numeral rather than upon an abstract semantic representation. Other evidence in favour of the use of asemantic transcoding comes from the existence of patients able to understand and to produce numerals but unable to transcode them. Given that, according to McCloskey, transcoding results from the succession of comprehension and production mechanisms, it is thus difficult to understand why, when in some patients both these comprehension and production processes are intact, transcoding is nevertheless impaired. Cipolotti (1995), for example, reported the patient SF with probable DAT who had severe difficulty in reading Arabic numerals aloud with an otherwise spared ability to recognize and understand them, and to produce similar verbal numerals in a non-reading context. The normal performance of SF in comprehension and production tasks suggests that his reading errors cannot be interpreted by a semantic deficit. This case therefore raises a central difficulty for models postulating a single semantic route for transcoding. To interpret this pattern of preserved and impaired processes, Cipolotti proposed to distinguish two independent routes for reading Arabic numerals aloud: one requiring an intermediate elaboration of number semantic representations

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and another a direct asemantic route. In this framework, SF’s impairment is suggested to result from a deficit at the level of the asemantic route. However, if the other route, that is, the semantic one, is spared, why does the patient not use it? To answer this recurrent question, Cipolotti (1995) speculated that the demands of the task influence the selection of the adequate route. In particular, the instruction “to read the Arabic numerals” would preferentially activate the “asemantic route”. Furthermore, she proposed that the activation of “the asemantic route” inhibits the use of the semantic one. Such an interpretation has been extended by Cohen and Dehaene (1995), who have shown that the reading of Arabic numerals in two cases of pure alexia is influenced by the task demands. Both these patients were dramatically impaired in reading words and multidigit Arabic numerals, and much less severely in reading single digits. The errors were mainly lexical. Yet, the authors observed an important variation in the reading performances when exactly the same Arabic numerals had to be processed in the context of a magnitude comparison (“read these two digits aloud and tell me which is larger”: 10–15% errors) or for a subsequent addition (“read these two digits aloud and give me their sum”: 31–45% errors). This suggests that, in the very first stages of digit identification, task demand would already influence the system to use one processing route rather than another. The authors explain these patterns by hypothesizing the existence of two distinct visual identification processes (one in each cerebral hemisphere) that contribute differently to reading, calculation, and comparison. Thus, like Cipolotti, the authors explain the competition between the impaired and intact reading routes by relying upon the task demands: calculation would bias the subjects to use their asemantic pathways, whereas a transcallosal semantic route would be privileged in comparison context. Although most studies on transcoding have postulated the autonomy of the verbal and the Arabic lexicon, some studies have investigated the hypothesis that the processing of the Arabic code is systematically mediated by the verbal code. The question asked is as follows: do tasks such as the comparison, reading, or use in operations of numbers presented in Arabic numerals induce the systematic activation of the verbal code? The hypothesis that the verbal code is automatically activated was suggested by Noël and Seron (1993), who described a patient who compared two numbers not on the basis of the Arabic numerals (e.g. 3) presented to him but on their verbal counterparts (e.g. /trwa/). The authors suggested that some subjects might employ a “preferred code” to access number-related knowledge. However, this hypothesis has never been further developed. The possible activation of verbal representations when processing Arabic numbers is also suggested by the observation of code intrusion errors in transcoding tasks. For instance, Thioux, Ivanoiu, Turconi, and Seron (1999) observed a patient with DAT who exhibited systematic intrusions of verbal numerals when she had to produce Arabic forms. These intrusions gave rise to mixed errors such as

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“three mille” instead of “3000” (trois mille/three thousand) or “15ZE” instead of 15 (quinze/fifteen) or even “h8t” instead of eight (huit/eight). In other neuropsychological group studies, intrusion errors have been observed in both directions (Arabic → verbal and vice versa), mainly in DAT patients (Kessler & Kalbe, 1996; Tegnér & Nybäck, 1990) but also in normal patients (Della Sala, Gentileschi, Gray, & Spinnler, 2002). These errors have been interpreted as being the result of an impairment in the transcoding mechanism itself as well as in the inhibitory processes. The inhibitory processes are postulated as being necessary to inhibit one code when the task requires the production of the other. In such a perspective, when subjects have to process a number in one code, the other code is automatically activated but not produced thanks to the inhibitory processes.

Arithmetical facts and arithmetic The knowledge of basic arithmetical facts such as 2 × 3 or 3 + 7 is an essential part of our general semantic knowledge and is of crucial importance in daily life situations. Since the beginning of the twentieth century, it has been well known that a left posterior parietal lesion may generate dyscalculic disorders. The first detailed description of a specific calculation disorder without language or intellectual disorders, or even disorders in reading or writing Arabic numerals, was reported by Lewandowsky and Stadelman (1908). Several years later, Warrington (1982) presented the case of a physician (DRC), who, although unable to do simple addition, subtraction, and division, presented no language disorders and remained able to read Arabic numerals. Interestingly, although the patient was unable to give the correct answers to simple arithmetical problems, he could propose approximate responses, that is, a number close in magnitude to the correct one. A similar dissociation between deficit in exact calculation with preservation of approximate calculation was described later by Dehaene and Cohen (1991). They observed a patient, NAU, who produced many errors in simple calculation, but was able in a verification task to reject incorrect responses far from the solution (such as 2 + 3 = 9), although he erred with incorrect but close responses (2 + 3 = 6). The authors thus proposed the existence of two calculation systems: one processing numbers as precise values and another one considering them as approximate magnitudes. This proposal of different representations of numbers remains at the centre of many debates (see below the section on number semantic representations). Certain specific patterns of errors produced by patients when solving simple arithmetical problems led McCloskey to propose a distinction between arithmetic problems solved by retrieval (2 × 3 or 5 + 6) and those solved through the use of a rule (product by 0 or by 1). In a multiple case study, Sokol and his collaborators (Sokol, McCloskey, Cohen, & Aliminosa, 1991; see also McCloskey, Aliminosa, & Sokol, 1991) reported several cases evidencing a double dissociation between retrieval and rule-based problems. For

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example, the patient HM produced 100% of errors on the 0×N problems, but he made only 3% of errors on N × M basic problems. The reverse dissociation was observed in another patient, CM, who correctly solved multiplication by 0 but made 17% of errors on N × M multiplication. The pattern of patient performances also revealed that the N × 0 or N × 1 problems were altogether either correct or missed in a regular way, while no such regularities were observed for the N × M problems. These data therefore suggest that the 0 and the 1 problems are solved by reference to a general rule (0 times any number is 0), while N × M problems are retrieved in memory and stored individually. For the rule-based problems, the patients in some cases have “lost” the rule, while in other cases they have applied an inadequate rule (for example, by systematically proposing N as the answer to the N × 0 problems). Deficits in arithmetical problem-solving have also been examined with regard to the nature of the operation. Some early anecdotic observations have indeed documented acalculic patients with arithmetical fact impairments specific to a particular type of operation. For example, Lewandowsky and Stadelman’s patient was clearly better at multiplication than addition, subtraction, and division problems (Lewandowsky & Stadelman, 1908). Singer and Low (1933) also described a patient who, while unable to solve division and subtraction problems, was good at addition and multiplication. However, these old data lack precision since they do not sufficiently describe in detail the stimuli, the procedures, and the results. Recently, Dagenbach and McCloskey (1992) have reported a patient whose performance in simple subtraction problems was significantly better than his performance in addition and multiplication problems. Since this observation was made, other patients with selective preservation of subtraction have been reported (Lampl, Eshel, Gilad, & Sarova-Pinhas, 1994; McNeil & Warrington, 1994; Pesenti, Seron, & Van der Linden, 1994), and, more importantly, various patterns of selectively preserved and impaired arithmetical facts according to the operation have been reported. For example, selective impairment of multiplication with better or entirely preserved addition and subtraction has been documented (Dehaene & Cohen, 1997; McCloskey et al., 1991). The reverse pattern—that is, a selective preservation of multiplication—has also been reported (Delazer & Benke, 1997). Finally, even a patient with selective impairment of simple division has been described by Cipolotti and de Lacy Costello (1995). These findings of highly selective impairment of arithmetical facts according to the operation has led to the formulation of two influential proposals regarding the organization and the retrieval of arithmetical facts in memory, one by McCloskey and colleagues (Dagenbach & McCloskey, 1992; McCloskey, 1992), and the other by Dehaene and Cohen (Dehaene, 1992; Dehaene & Cohen, 1995, 1997). According to McCloskey and his colleagues, retrieving arithmetical facts involves first converting the problem, either verbally (“four plus three”) or by Arabic digits (“5 + 7”), into an abstract and amodal representation. This representation is then used to activate in memory the corresponding

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arithmetical fact. The model also postulates that each arithmetical fact is stored as a distinct representation and that the facts are segregated in memory according to the operation. There are thus separate representations for addition, multiplication, subtraction, and division problems. Such a model may, according to the location and extension of the brain lesion, predict any pattern of dissociation between preserved and impaired operations. According to Dehaene’s triple code model, numbers are represented in the human brain in three different formats: as a sequence of digits in the visual Arabic representation, as number words in the auditory-verbal representation, and as magnitude in the analogical representation. In this perspective, the arithmetical facts that have been learned by rote, such as simple addition and the multiplication table, are stored in verbal representations, while subtraction and division require the activation of the magnitude representation. Consequently, there are two different routes for simple arithmetic problems: a direct asemantic route, specialized in storing and retrieving the rote verbal knowledge of arithmetic tables, and an indirect semantic route, specialized in quantitative processing. In the asemantic route, the problem (whatever its format) is first transcoded in an internal verbal representation. This representation is then used to trigger completion of this word sequence by rote verbal memory. This hypothesis is derived from the observation that multiplication and simple addition have been systematically learned by rote at school as rote verbal sequences. On the contrary, subtraction, division, and large addition (larger than 10) have not been learned through intensive rote verbal learning; their resolution thus requires a semantic manipulation of the corresponding quantities, termed by the authors to be “semantic elaboration”. In such a model, some specific associations and dissociations between the four operations are privileged: simple addition and multiplication may have a common fate if there is an impairment of the asemantic route (that is, a degradation of number verbal memories), while deficits in complex addition, division, and subtraction may be more dependent on an impairment in the semantic route. The prediction of the triple code is, however, slightly more complex, as the authors also add that subjects may in some cases (for example, for addition) use both the semantic and the asemantic route in solving arithmetical problems. Consequently, Dehaene suggests that it would be simplistic to expect a full dissociation between the arithmetic problems according to the operation. In any case, the best evidence of an impairment of the semantic route would be a deficit in subtraction problems and in large addition, while the clearest evidence of an impairment of the asemantic route would be a deficit in very simple multiplication. Moreover, given the expected common fate of the operation solved through rote verbal memories, the model does not expect to find patients with a selective impairment or selective preservation of addition relative to multiplication and subtraction. Consistent with these predictions are reports of selective impairments in multiplication relative to subtraction (Dagenbach & McCloskey, 1992; Dehaene & Cohen, 1997; Pesenti et al., 1994) and of selective impairment of subtraction relative to multiplication

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(Dehaene & Cohen, 1997; Delazer & Benke, 1997). Also in agreement with the proposal that multiplication is mediated through verbal associations is the finding that several patients present an association of language disorders and impairment in multiplication (Dagenbach, & McCloskey, 1992; Dehaene & Cohen, 1991, 1997; Delazer & Bartha, 2001; Delazer, Girelli, Semenza, & Denes, 1999; Girelli, Delazer, Semenza, & Denes, 1996; Pesenti et al., 1994; Sokol et al., 1991), whereas those with preserved multiplication tend to have intact linguistic skills (Dehaene & Cohen, 1997; Delazer & Bartha, 2001). However, some cases reveal patterns of performance that do not support Dehaene and Cohen’s model. For example, Van Harskamp and Cipolotti (2001) have described a patient (FS) who was specifically impaired in the resolution of simple and complex addition, but perfect in other operations. Such a selective deficit points, on the one hand, to an unexpected dissociation between simple addition and simple multiplication (the asemantic route), and, on the other hand, to a dissociation between complex addition and subtraction (the semantic route). The same authors (Van Harskamp, Rudge, & Cipolotti, 2002) have also described a patient with a deficit in single-digit subtraction who did not present any difficulty in quantity manipulation. Such patterns of dissociations are more compatible with a model postulating selective damage in a memory network segregated according to each operation. Finally, Whalen and his collaborators (Whalen, McCloskey, Lindenmann, & Bouton, 2002) have reported two patients that often retrieved the correct answer to simple arithmetic problems from memory, although they were unable to generate the phonological representation of either the arithmetic problem or the answer to that problem. This pattern of performance is not compatible with a model postulating that arithmetic problems, especially simple addition and multiplication, are stored exclusively in memory in a phonological format. There is thus now no agreement on the format of the arithmetical facts in memory. Although Dehaene’s proposal for verbal storage has not been definitively established, it seems reasonable to suggest that the storage and retrieval of arithmetical facts are related to the surface characteristics of the stimuli used during the learning phase, as has been demonstrated in normal subjects (Spelke & Tsivkin, 2001). Beyond the analysis of arithmetical skills, some authors, especially Margareth Delazer, have emphasized the need to look into the understanding of arithmetical operations (Hittmair-Delazer, Semenza, & Denes, 1994). This level of processing—termed “conceptual” by Delazer—concerns the understanding of arithmetical operations and the laws pertaining to these operations. With such a level of analysis in mind, Delazer had reported a study of a patient, BE, who developed aphasia and calculation deficit after a left haemorrhagic lesion, but who compensated for his calculation deficit by complex strategies. The deficit of BE was not global since he was still able to retrieve the results of addition and subtraction, and to retrieve multiplication by two and also some arithmetical problems with three, four, and five as operands. He was, however, completely unable to retrieve the result from

214 Seron memory of larger multiplication and division problems. When BE was asked to solve the arithmetic problems he could not retrieve from memory, he started to develop strategies that consisted of breaking the complex problems down into smaller ones in the range of his preserved abilities. In the development of such decomposition strategies for multiplication and division, BE used his preserved knowledge of the mathematical principles tied to these operations. For example, to resolve multiplication with six as an operand, BE multiplied the second operand by 10, divided by two, which was no problem for him, and finally added the second operand. Interestingly, BE always seemed to have good intuition as to which strategies were useful and economic for solving the problem presented. He always chose the strategies that simplified the solution process. He demonstrated a dissociation between impaired arithmetical fact knowledge and intact conceptual knowledge that allowed him to use back-up strategies based on mathematical principles. The proposal that conceptual knowledge and fact knowledge are mediated by separate cognitive mechanisms is reinforced by the observation of another patient, DA, who, although unable to answer from memory half of basic additions, subtractions, multiplications, and divisions, was able to answer algebraic equations perfectly (Hittmair-Delazer, Sailer, & Benke, 1995). He could also enumerate the steps required to solve arithmetic text problems though he was unable to perform the actual computational steps themselves. These cases considered together, as well as other but more anecdotal reports, show that the understanding and the use of arithmetical principles can be considered as different from and independent of stored fact knowledge.

The semantic representation of numbers There is much debate over the representation of numbers in the brain. How is our knowledge of numerosities, numbers, and arithmetic represented in the brain? On the one hand, there is the proposition that our number knowledge is rooted in a basic and innate “number sense” (Dehaene, 2001) or “number organ” (Butterworth, 1999) already present in babies and that we share with other animal species. According to this view, babies are equipped with a cognitive component that allows them to represent the number of events and to operate on these representations by adding or subtracting small numbers. It has been suggested that the format of these number representations may be analogue magnitudes, akin to a number line (Meck & Church, 1983). Another proposal is that numbers are represented in infants by a unique symbol. For each object in the set, a unique representation is opened, the resulting representation implicitly representing the number in the array. The symbol created for each object has been called an “object file” (Feigenson, Carey, & Hauser, 2002; Simon, 1997, 1999). These two representations present different properties. The object file representation is subject to a major

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size limitation, as only small sets can be individuated in parallel and stored in short-term memory. In contrast, large sets can be encoded by analogue magnitudes, but discrimination is subject to Weber’s law such that only sets with a constant ratio can be discriminated. Although there is still competition between the analogue and the object file representations to determine which one is at the origin of symbolic arithmetic, in neuropsychology, only the analogue magnitude representation has received any consideration. Much research in psychology and in neuropsychology has converged to sustain the existence of an analogue magnitude representation for numerosities in the human brain. The main evidence for such analogue magnitude representation in man is deduced from the fact that a distance and a size effect3 has been observed regularly even when the brain processes numbers presented in symbolic notations (Arabic digits or verbal numerals) (Buckley & Gilman, 1974; Dehaene, 1996; Dehaene, Dupoux, & Mehler, 1990; Moyer & Landauer, 1967). This suggests that, even when presented in a symbolic format, number processing converges to the analogue quantity representation. It has also been demonstrated that such access may be automatic, since it is found even when the subjects do not have to process the numbers semantically (Dehaene & Akhavein, 1995) or in priming experiments (Brysbaert, 2005; Koechlin, Naccache, Block, & Dehaene, 1999). Much research into brain-damaged patients and brain-imaging studies has also converged to indicate that the inferior parietal region of the brain may well be the critical area that, if impaired, creates a deficit in the semantic representation of numbers. Indeed, it is well known that a lesion of the inferior parietal region of the left hemisphere results in a deficit in number processing that constitutes, together with other associated disorders, the Gerstmann syndrome (Gerstmann, 1940; Hécaen, Angerlergues, & Houiller, 1961; Henschen, 1926; Mayer, Martory, Pegna, Landis, Delavelle, & Annoni, 2000). There are, however, not many cases with a semiology confined to the interpretation of number semantics without disorders in the recognition of the notations. The patient MAR described by Dehaene and Cohen (1997) is such an exception. The patient was able to read and write Arabic numerals correctly, but he was impaired in number comparison, simple calculation, and approximate judgment of magnitude. Aside from these pathological data, brain imaging also furnishes some evidence as to the crucial role of the intraparietal sulcus for the manipulation and the semantic representation of numerical quantity. In number comparison tasks, the activation is essentially bilateral: some loci of activation have also been observed in the supramarinal gyrus and in the angular gyrus, but the largest and most frequent activations have been observed in the intraparietal sulcus (Chochon, Cohen, Van de Moortele, & Dehaene, 1999; Dehaene et al., 1996; Rickard, Romero, Basso, Wharton, Flitman, & Grafman, 2000). Furthermore, the intraparietal activations have been shown to be modulated by the distance between the numbers (Pinel, Dehaene, Rivière, & Le Bihan, 2001), and they have also been observed when numbers are processed unconsciously (Naccache & Dehaene, 2001). This

216 Seron activation is bilateral with an either left or right dominance according to the reference task (Zago, & Pesenti, 2004). The possible location into the parietal lobe of the semantic representation of numbers has induced some authors to ask, “Why are numbers located there”? The answer is not simple and at present certainly not definitive. One suggestion is that this inferior intraparietal region is genetically determined to process specifically numerosities. The intraparietal region is viewed as the biological basis of the “number sense”, which is qualified as a biologically determined category of knowledge. In such a perspective, the parietal localization is viewed as highly specific and not easily transferred to other brain regions. This constitutes, for example, the innate and category-specific position of Dehaene (1997). In another perspective, it is suggested that the parietal localization of the analogue magnitude representation is linked with several functions that rely on estimating magnitudes of one type or another. This view emphasizes that, in addition to spatial computations coded in action coordinates (Stein, 1992), the parietal cortex is also important for numerosity estimation, temporal judgment (Critchley, 1953), and size judgments (Walsh, 2003). In this direction, a brain-imaging study done by Fias and his collaborators (Fias, Lammertyn, Reynvoet, Dupont, & Orban, 2003) showed that when subjects are asked to indicate whether a difference of orientation between two oblique gratings is larger or smaller than a fixed standard, significant loci of activation are found in the left parietal lobule and left ventral premotor cortex consistent with results obtained in numberprocessing tasks. In a third orientation, results from brain-imaging studies indicate that number-processing activates a network including not only parietal regions but also premotor cortex, as shown in positron emission tomography (PET) (Chochon et al., 1999; Pesenti, Thioux, Seron, & de Volder, 2000; Zago, Pesenti, Mellet, Crivello, Mazoyer, & Tzourio-Mazoyer, 2001) and functional magnetic resonanc imaging (fMRI) (Pinel, Le Clec’H, van de Moortele, Naccache, Le Bihan, & Dehaene, 1999; Stanescu-Cosson, Pinel, Van de Moortele, Le Bihan, Cohen, & Dehaene, 2000). As the premotor activation in number processing is close to the representation of fingers, it has been suggested (Zago et al., 2001) that the premotor activity represents the trace of a developmental finger-counting strategy used for numerical acquisition. Although this interpretation is still speculative, it has reactivated the studies on the relationships between finger discrimination and numerical abilities. Finally, an involvement of the parietal lobe has also been observed in the coding of order information in working memory. The fact that the parietal activations overlapped those involved in number processing has led to the suggestion that the underlying representation of order and numbers may share some common process (Marshuetz, Smith, Jonides, DeGutis, & Chenevert, 2000). However, we also must emphasize that certain authors have questioned the specificity of the activations observed during numbercomparison tasks, and it is suggested that activation in the intraparietal sulcus during number-comparison tasks may simply reflect a parietal role in

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maintaining a representation of a possible motor response (Gobel, JohansenBerg, Behrens, & Rushworth, 2004). Although such an argumentation remains possible, it does not correspond to the data (even if they are rare) indicating that a left parietal lesion may result in an impairment of number semantics. Aside from the analogue model for number representation, human beings also acquire and process verbal and Arabic numerals as well as many other conventional arithmetical signs. These words and symbols constitute symbolic arithmetic, which is also represented in some way in the brain. The point we want to discuss here is not the format-dependent representation of the verbal numerals or Arabic numerals in the brain, but rather the representation of their meaning. The defenders of the analogue representation of numbers have done a lot of research to find the signature of the analogue representation when numerate adults process symbolic arithmetic, and, given that both the distance and size effects have been observed with symbolic notations, it has been proposed that the use of numerical symbols is rooted in brain circuits devoted to presymbolic processing of numerosities. The general idea is that the arithmetic symbols are in some way connected to the compressed analogue magnitude representation and that such a connection brings some precision to the analogue representation.4 But as we have discussed elsewhere (Fayol & Seron, 2005), this view is clearly insufficient. In fact, if a compressed number line may constitute an adequate support for approximate arithmetic, it is clearly not a sufficiently strong structure to capture the essence of symbolic arithmetic. First of all, since the analogue numerical representations become ever more approximate as numerosity increases, this type of model does not possess any precise semantic representation of large numbers. Another difficulty in conceiving analogue representation as the sole semantic representation of numerosity lies in the fact that the numerical representation is unitary, since it corresponds either to the length of the activated segment (Gallistel & Gelman, 1992) or to a position marked by a pattern of activation (Dehaene, 1992). Moreover, this type of representation fails to capture the base-10 organization of the notation of the Arabic system and does not represent the multiplicative and additive relations that are specific to verbal notation. Finally, when semantic representation is understood as a type of compressed continuum, it is unable to represent the equivalence of numerical distances between numbers situated at different points within the continuum, since it violates the equidistance property of the number system. Thus, unless we posit a considerable extension of the properties of the number line, it is difficult to see how this type of representation of numerosity can represent the precise meanings that are associated with large numbers and expressed by the verbal and Arabic notational systems and the corresponding calculations, in particular with regard to the specification of the results. One of the key functions of language and of notational systems is, in effect, to permit the precise representation and processing of quantities which go beyond the

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discriminatory limits of our perceptual systems and the imprecision of our elementary quantification processes (counting and estimation). The present focus of research into presymbolic arithmetic and into the socalled number sense has been highly detrimental to the study of the properties of the symbolic number system per se. Currently in neuropsychology, two main proposals concerning symbolic number representations have been proposed: McCloskey’s (1992) base-10 semantic system and the verbal semantic system developed by Power and Longuet-Higgins (Power & LonguetHiggins, 1978; Power & Dal Martello, 1990). McCloskey considers that the internal semantic representation of numbers is assumed to specify in an abstract form the basic quantities in a number, and the power of 10 associated with each. For example, an Arabic number such as 6042 generates through some comprehension processes a semantic representation of the form {6} 10 exp2; {4} 10 exp1; {2} 10exp0. The digits in the braces indicate the quantity representations and 10EXPn indicates a power of 10. This notation is adopted to avoid any confusion with either the verbal or the Arabic representations. In McCloskey’s model, the semantic representations are precise. They are also componential since the quantity is expressed by a combination of the basic quantities and their associated powers of 10. The semantic representations are also abstract, that is, independent of the notational system for numbers (Arabic or verbal codes), and they are amodal, the same representations being activated whatever the channel of presentation of numbers (visual for Arabic or auditory for verbal numerals). Although this model has had some success, it has encountered two important limitations. On the one hand, it cannot easily explain the two main effects usually encountered in number semantic tasks (such as number magnitude comparison): the distance effect and the size effect. On the other hand, the model has been elaborated exclusively in relation to tasks concerned by symbolic arithmetic. For example, there is no indication as to how such a semantic representation may be activated by non-symbolic numerosities such as a collection of dots. The argument is not to affirm that McCloskey’s model is intrinsically unable to represent concrete numerosities or explain the distance or the size effects; the point is that the representation of concrete numerosities has not been systematically addressed by McCloskey and his collaborators. Another model, also using exact and abstract semantic representations for numbers, has been proposed by Power and Dal Martello (1990). Contrary to McCloskey’s model, this model does not assume a base-10 representation, but rather a semantic representation that reflects the lexical structure of the verbal numeral system and its product (two hundred means two times hundred) and sum (hundred and two means hundred plus two) relationships. For example, the numeral “three thousand and forty-two” would be represented by (C1000 × C3) + (C10 × C4) + C2, in which Ci corresponds to the semantic concept referring to the quantity “i”, and the operator “+” and “×” the sum and product relations. In fact, this model is very close to McCloskey’s model,

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since it shares both the idea of a precise and componential representation of the quantities as well as the same limitation in the representation of symbolic arithmetic.5 In fact, while Power and Dal Martello’s model has been less influential in neuropsychology, it has nevertheless been used frequently to interpret the errors made by brain-damaged patients or by children in transcoding tasks (Lochy, Pillon, Zesiger, & Seron, 2002).

Conclusions Much work remains to be done before we understand how the human brain is able to represent many of the properties of the symbolic number systems per se, and there currently remains a gap in psychology and in neuropsychology between the research that has focused on symbolic arithmetic and the research that has tried to establish the biological basis of our “number sense” or “number organ”. If we are to bridge this gap, two directions of research must be emphasized: research firstly on order processing and secondly on the use of fingers. Research on order processing and representations is critical, because order is one of the fundamental characteristics of the symbolic systems (Arabic or verbal). In these notation systems, the iconic representation of magnitude is transformed by the order of the elements in the sequence. The symbolic systems encode the quantity in terms of the rank occupied by the signs in the verbal or the Arabic sequences (one (1), two (2), three (3), four (4), five (5), etc.). “Six” (6) refers to a larger quantity than “five” (5) because it comes in the sequence after “five” (5). However, there is nothing in the term “six” (or the sign “6”) to indicate that the cardinal value to which it refers is greater than “five” (5). The name or the Arabic signs provide no information about the increase in the quantities. The transformation of magnitude into order relations is thus an essential aspect of symbolic arithmetic. As rightly underlined by Wiese (2003), the numeral verbal system and the Arabic system constitute a progression; that is, their sequence can be characterized by discrete elements ordered along a relation with specific properties (antireflexive, asymmetric, and transitive). Secondly, the reason to look at fingers is of course related to the association of a deficit in finger identification together with the impairment in number processing, sometimes observed in the Gerstmann syndrome. But more generally, it should be stressed that the use of fingers as a representative medium may play an intermediary role between presymbolic and symbolic number representations. There is indeed a body of different but converging evidence to support the idea that fingers are involved in the development of some procedural and declarative knowledge in arithmetic. Children use their fingers to count before they are systematically taught arithmetic (Butterworth, 1999), and in the cultures within which counting procedures exist, finger counting precedes or accompanies the development of the symbolic procedures (Dantzig, 1962). Brain-damaged adult patients suffering from severe acalculia exhibit a set of associated disorders (the Gerstmann syndrome), a key element of which is the loss of finger

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sense (digital agnosia) (Cipolotti et al., 1991; Gerstmann, 1940; Mayer et al., 2000). At the developmental level, bidirectional links have been established between the presence of digital agnosia and arithmetical deficit (Kinsbourne & Warrington, 1962, 1963; Pebenito, 1987; Rourke, 1993; Strauss & Werner, 1938). And the hypothesis of a functional link between digital representations and numerical representations has been further reinforced by the work undertaken by Fayol and his co-workers (Fayol, Barrouillet, & Marinthe, 1998), who have shown in a longitudinal study that the perceptuotactile performances evaluated at 5 years of age are better predictors than the general development scores of subsequent arithmetical performance at 6 and then 8 years of age. Finally, in various functional imaging studies (Dehaene et al., 1996; Pinel et al., 1999; Pesenti et al., 2000), the involvement of the left precentral gyrus and close areas in the frontal lobes has been repeatedly observed when subjects are asked to perform simple arithmetical tasks. Such recurrent associations have led Pesenti et al. (2000) to propose that “the joint activation of these frontal areas with the parietal ones may reflect the involvement of the finger movement network that might underlie finger counting (Butterworth, 1999; Simon, 1999), one of the basic numerical learning strategies spontaneously developed by children (Fuson, 1988)” (Pesenti, Thioux, Seron, & de Volder, 2000, p. 474). These data have therefore led Butterworth to suggest that “as the child grows and develops, the subitizing circuits in the inferior parietal link with the finger circuits in the intraparietal sulcus. The fingers, therefore, gain an extended representation by this link: they come to represent the numerosities” (1999, p. 250). A number of characteristics of the finger-based representations make these a powerful candidate for the establishment of such a link. The fingers, like language, have an abstract character, since the same pattern of raised fingers can equally well represent three giraffes, three toys, or three elements in an argument. However, whereas language permits the same type of abstraction, finger representations retain an analogue character since they preserve the one-to-one matching relation between the represented set and the fingers used to represent it, given that raised fingers have an analogue relation with numerosity. Fingers also have the advantage that they can act as a support for the subject’s actions since they can be mobilized in concrete situations in order to represent the various additive and multiplicative procedures. Finally, it is perfectly conceivable that the joint use of the fingers and the hands also constitutes a useful representation that plays a mediating role in the understanding of base-10 (or, indeed, base-5). We believe that the external representations that make use of fingers and that are actively incorporated in children’s activities could play an important role in establishing these abstract mental representations. However, although these particular structural and processing aspects of finger use make fingers plausible candidates as the missing link between presymbolic and symbolic representations, a lot of work is still necessary to establish more precisely their role in math cognition.

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Notes 1 Both numeric systems may be described in terms of an ensemble of lexical primitives plus some combinatorial rules. The Arabic system is composed of a small set of symbols, the digits from 1 to 9, which represent numerosities that are smaller than the base. To represent larger quantities, it uses a positional notation. In a multidigit number, the position of each digit indicates the power of the base by which it must be multiplied (e.g. 432 = 4 × 102 + 3 × 101 + 2 × 100). The digit 0 indicates the absence of a value for a given power of 10 in the number. The verbal numeral system is also composed of lexical primitives, which can be grouped into different lexical classes (the units from one to nine, the Tens from ten to ninety, and the Teens from eleven to nineteen, as well as some multipliers such as hundred, thousand, and million). The lexical units are embedded in two kinds of semantic relationships, the multiplicative relations, such as “two hundred” or “five thousand”, and the additive relations: “one hundred and two”, “one thousand and forty”, or “sixty-three”. In English and in French, any numerosity can thus be decomposed as a tree with successive embeddings of multiplicative and additive relationships (Power & Longuet-Higgins, 1978). 2 In French from France, the verbal sequence “quatre-vingt dix sept”, literally “fourtwenty-ten-seven”, represents “97”. 3 The distance effect in number-comparison tasks corresponds to the fact that subjects take more time and make more errors responding when the two numbers are numerically close (e.g. 8 vs. 9) than when they are further apart (e.g. 2 vs. 9). The size effect corresponds to the fact that at the same distance, small numbers (e.g. 5 vs. 7) are easier to compare than larger ones (e.g. 25 vs. 27). 4 For a simulation study that presents a concrete proposal on the linkage between higher-order numerical cognition and more primitive numerical abilities, see Verguts and Fias (2004). 5 The two models differed, however, in the way they represent the numerals above 9999. For example, twenty-one thousand would be represented in McCloskey’s model by (2)10EXP4, (1)10EXP3, which is formally equivalent to (C10 000 × C2) + (C1000 × C1), whereas Power et al.’s model does not postulate the existence of a concept such as C10 000, which does not correspond to a lexical primitive in French or English. A second difference concerns the numerals between 1100 and 1999, which can be expressed through hundred or thousand verbal structures. For example, 1200 can be expressed either by “twelve hundred” or by “one thousand and two hundred”. In McCloskey’s model, such a change in the verbal structure makes no difference at the semantic level, whereas these two verbal structures activate different representations in Power et al.’s model.

References Antell, S. E., & Keating, D. P. (1983). Perception of numerical invariance in neonates. Child Development, 54, 695–701. Ashcraft, M. H. (1992). Cognitive arithmetic: A review of data and theory. Cognition, 44, 75–106. Balakrishman, J. D., & Ashby, F. G. (1992). Subitizing: Magical numbers or mere superstition? Psychological Review, 54, 80–90. Barth, H., Kanwisher, N., & Spelke, E. (2003). The construction of large number representations in adults. Cognition, 86, 201–221. Benson, D. F., & Denckla, M. B. (1969). Verbal paraphasia as a source of calculation disturbance. Archives of Neurology, 21, 96–102.

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Berger, H. (1926). Über Rechenstörungen bei Herderkrankungen des Grosshirns. Archiv für Psychiatrie und Nervenkrankheiten, 78, 238–263. Brysbaert, M. (2005). Number recognition in different formats. In J. I. D. Campbell (Ed.), Handbook of mathematical cognition (pp. 23–43). Hove: Psychology Press. Buckley, P. B., & Gilman, C. B. (1974). Comparisons of digits and dot patterns. Journal of Experimental Psychology, 103, 1131–1136. Butterworth, B. (1999). The mathematical brain. London: Macmillan. Campbell, J. I. D., & Clark, J. M. (1988). An encoding-complex view of cognitive number processing: Comment on McCloskey, Sokol, and Goodman (1986). Journal of Experimental Psychology: General, 117, 204–214. Campbell, J. I. D., & Clark, J. M. (1992). Cognitive number processing: An encodingcomplex perspective. In J. I. D. Campbell (Ed.), The nature and origins of mathematical skills (pp. 457–492). Amsterdam: Elsevier. Carey, S. (2001). Bridging the gap between cognition and developmental neuroscience: The example of number representation. In C. A. Nelson & M. Luciana (Eds.), Handbook of developmental cognitive neuroscience (pp. 415–431). Cambridge, MA: MIT Press. Chochon, F., Cohen, L., Van de Moortele, P.-F., & Dehaene, S. (1999). Differential contributions of the left and right parietal lobules to number processing. Journal of Cognitive Neuroscience, 11, 617–630. Cipolotti, L. (1995). Multiple route for reading words, why not numbers? Evidence from a case of Arabic numeral dyslexia. Cognitive Neuropsychology, 12, 313–342. Cipolotti, L., & Butterworth, B. (1995). Toward a multiroute model of number processing: Impaired number transcoding with preserved calculation skills. Journal of Experimental Psychology: General, 124, 375–390. Cipolotti, L., & de Lacy-Costello, A. L. (1995). Selective impairment for simple division. Cortex, 31, 433–449. Cipolotti, L., Butterworth, B., & Denes, F. (1991). A specific deficit for numbers in a case of dense acalculia. Brain, 114, 2619–2637. Cipolotti, L., Butterworth, B., & Warrington, E. (1994). From one thousand nine hundred and forty-five to 1000,945. Neuropsychologia, 32, 503–509. Cohen, L., & Dehaene, S. (1991). Neglect dyslexia for numbers? A case report. Cognitive Neuropsychology, 8, 39–58. Cohen, L., & Dehaene, S. (1995). Number processing in pure alexia: The effect of hemispheric asymmetries and tasks demand. Neurocase, 1, 121–137. Cohen, L., Dehaene, S., & Verstichel, P. (1994). Number words and number nonwords: A case of deep dyslexia extending to arabic numerals. Brain, 117, 267–279. Collignon, R., Leclercq, C., & Mahy, J. (1977). Étude de la sémiologie des troubles du calcul observés au cours des lésions corticales. Acta Neurologica Belgica, 77, 257–275. Critchley, M. (1953). The parietal lobes. London: Hafner Press. Dagenbach, D., & McCloskey, M. (1992). The organization of arithmetic facts in memory: Evidence from a brain-damaged patient. Brain and Cognition, 20, 345–366. Dahmen, W., Hartje, W., Bussing, A., & Sturm, W. (1982). Disorders of calculation in aphasic patients: Spatial and verbal components. Neuropsychologia, 20, 145–153. Dantzig, T. (1962). Number: The language of science. London: George Allen & Unwin. Dehaene, S. (1989). The psychophysics of numerical comparison: A reexamination of apparently incompatible data. Perception and Psychophysics, 45, 557–566. Dehaene, S. (1992). Varieties of numerical abilities. Cognition, 44, 1–42.

12. The neuropsychology of calculation

223

Dehaene, S. (1996). The organization of brain activations in number comparison: Event-related potentials and the additive factors methods. Journal of Cognitive Neuroscience, 8, 314–326. Dehaene, S. (1997). The number sense: How the mind creates mathematics. New York: Oxford University Press. Dehaene, S. (2001). Précis of the number sense. Mind and Language, 16, 16–36. Dehaene, S., & Akhavein, R. (1995). Attention, automaticity, and levels of representation in number processing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 314–326. Dehaene, S., & Changeux, J. P. (1993). Development of elementary numerical abilities: A neuronal model. Journal of Cognitive Neurosciences, 5, 390–407. Dehaene, S., & Cohen, L. (1991). Two mental calculation systems: A case study of severe dyscalculia with preserved approximation. Neuropsychologia, 29, 1045–1074. Dehaene, S., & Cohen, L. (1994). Dissociable mechanisms of subitizing and counting: Neuropsychological evidence from simultagnosic patients. Journal of Experimental Psychology, 20, 958–975. Dehaene, S., & Cohen, L. (1995). Towards an anatomical and functional model of number processing. Mathematical Cognition, 1, 83–120. Dehaene, S., & Cohen, L. (1997). Cerebral pathways for calculation: Double dissociations between Gerstmann’s acalculia and subcortical acalculia. Cortex, 33, 219–250. Dehaene, S., Dupoux, E., & Mehler, J. (1990). Is numerical comparison digital? Analogical and symbolic effects in two-digit number comparison. Journal of Experimental Psychology: Human Perception and Performance, 16, 626–641. Dehaene, S., Tzourio, N., Frak, V., Raynaud, L., Cohen, L., Mehler, J., et al. (1996). Cerebral activations during number multiplication and comparison: A PET study. Neuropsychologia, 34, 1097–1106. Delazer, M., & Bartha, L. (2001). Transcoding and calculation in aphasia. Aphasiology, 15, 649–679. Delazer, M., & Benke, T. (1997). Arithmetic facts without meaning. Cortex, 33, 697–710. Delazer, M., & Denes, G. (1998). Writing arabic numerals in an agraphic patient. Brain and Language, 64, 257–266. Delazer, M., & Girelli, L. (1997). When “Alfa Romeo” facilitates 164: Semantic effects in verbal number production. Neurocase, 3, 461–475. Delazer, M., & Girelli, L. (2004). Le modèle modulaire de McCloskey. Ch. 2. In M. Pesenti & X. Seron (Eds.), La Cognition numérique (pp. 45–67). Paris: Hermes Science, Lavoisier. Delazer, M., Girelli, L., Semenza, C., & Denes, G. (1999). Numerical skills and aphasia. Journal of the International Neuropsychological Society, 5, 213–221. Della Sala, S., Gentileschi, V., Gray, C., & Spinnler, H. (2002). Intrusion errors in numerical transcoding by Alzheimer patients. Neuropsychologia, 38, 768–777. Deloche, G., & Seron, X. (1982a). From one to 1: An analysis of a transcoding process by means of neuropsychological data. Cognition, 12, 119–149. Deloche, G., & Seron, X. (1982b). From three to 3: A differential analysis of skills in transcoding quantities between patients with Broca’s and Wenicke’s aphasia. Brain, 105, 719–733. Deloche, G., & Seron, X. (1987). Numerical transcoding: A general production model. In G. Deloche & X. Seron (Eds.), Mathematical disabilities: A cognitive

224

Seron

neuropsychological perspective ( pp. 137–170). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Fayol, M., Barrouillet, P., & Marinthe, C. (1998). Predicting arithmetical achievement from neuropsychological performance: A longitudinal study. Cognition, 68, B63–B70. Fayol, M., & Seron, X. (2005). About numerical representations; insights from neuropsychological, experimental, and developmental studies. In J. I. D. Campbell (Ed.), Handbook of mathematical cognition (pp. 3–22). Hove: Psychology Press. Feigenson, L., Carey, S., & Hauser, M. (2002). The representations underlying infants’ choice of more: Object files versus analog magnitudes. Psychological Science, 13, 150–156. Feigenson, L., Carey, S., & Spelke, E. (2002). Infants’ discrimination of number vs. continuous extent. Cognitive Psychology, 44, 33–66. Ferro, J. M., & Botelho, M. A. S. (1980). Alexia for arithmetical signs. A cause of disturbed calculation. Cortex, 16, 175–180. Fias, W., Lammertyn, J., Reynvoet, B., Dupont, P., & Orban, G. A. (2003). Parietal representation of symbolic and non-symbolic magnitude. Journal of Cognitive Neuroscience, 15, 47–56. Fuson, K. C. (1988). Children’s counting and the concepts of number. New York: Springer. Gallistel, C. R., & Gelman, R. (1992). Preverbal and verbal counting and computation. Cognition, 44, 43–74. Gerstmann, J. (1940). Syndrome of finger agnosia, disorientation for right and left, agraphia, and acalculia. Archives of Neurology and Psychiatry, 44, 398–408. Girelli, L., & Delazer, M. (2001). Numerical abilities in dementia. Aphasiology, 15, 681–694. Girelli, L., Delazer, M., Semenza, C., & Denes, D. (1996). The representation of arithmetical facts: Evidence from two rehabilitation studies. Cortex, 32, 49–66. Gobel, S. M., Johansen-Berg, H., Behrens, T., & Rushworth, M. F. S. (2004). Response-selection-related parietal activation during number comparison. Journal of Cognitive Neuroscience, 16, 1–17. Halpern, C., McMillan, C., Moore, P., Dennis, K., & Grossman, M. (2003). Calculation impairment in neurodegenerative diseases. Journal of the Neurological Sciences, 208, 31–38. Hauser, M. D., Carey, S., & Hauser, L. B. (2000). Spontaneous number representation in semi-free-ranging rhesus monkeys. Proceedings of the Royal Society of London. Series B, Biological Sciences, 267, 829–833. Hécaen, H., Angerlergues, R., & Houiller, S. (1961). Les variétés cliniques des acalculies au cours des lésions rétrorolandiques: Approche statistique du problème. Revue Neurologique, 2, 85–113. Henschen, S. E. (1926). On the function of the right hemisphere of the brain in relation to the left in speech, music and calculation. Brain, 49, 11–123. Hinrichs, J. V., Berie, J. L., & Mosell, M. K. (1982). Place information in multidigit number comparison. Memory and Cognition, 10, 487–495. Hittmair-Delazer, M., Sailer, U., & Benke, Th. (1995). Impaired arithmetic facts but intact conceptual knowledge—a single case study of dycalculia. Cortex, 31, 139–147. Hittmair-Delazer, M., Semenza, C., & Denes, F. (1994). Concepts and facts in calculation. Brain, 117, 715–728.

12. The neuropsychology of calculation

225

Hurford, J. R. (1987). Language and number. Oxford: Basil Blackwell. Kaufmann, L., Montanes, P., Jacquier, M., Matallana, D., Eibl, G., & Delazer, M. (2002). About the relationship between basic numerical processing and arithmetics in early Alzheimer’s disease: A follow-up study. Brain and Cognition, 48, 398–405. Kessler, J., & Kalbe, E. (1996). Written numeral transcoding in patients with Alzheimer’s disease. Cortex, 32, 755–761. Kinsbourne, M., & Warrington, E. (1962). A study of finger agnosia. Brain, 85, 47–66. Kinsbourne, M., & Warrington, E. (1963). The developmental Gerstmann syndrome. Archives of Neurology, 8, 490–501. Koechlin, E., Naccache, L., Block, E., & Dehaene, S. (1999). Primed numbers: Exploring the modularity of numerical representations with masked and unmasked semantic priming. Journal of Experimental Psychology: Human Perception and Performance, 25, 1882–1905. Lampl, Y., Eshel, Y., Gilad, R., & Sarova-Pinhas, I. (1994). Selective acalculia with sparing of the subtraction process in a patient with left parietotemporal haemorrhage. Neurology, 44, 1759–1761. Lewandowsky, M., & Stadelman, E. (1908). Über einen bemerkenswerten Fall von Hirnblutung und über Rechenstöreungen bei Herderkrankung des Gehirns. Journal für Psychologie und Neurologie, 11, 249–265. Lochy, A., Pillon, A., Zesiger, P., & Seron, X. (2002). Verbal structure of numerals and digits handwriting: New evidence from kinematics. Quarterly Journal of Experimental Psychology, 55A, 263–288. Marshuetz, C., Smith, E. E., Jonides, J., DeGutis, J., & Chenevert, T. L. (2000). Order information in working memory: fMRI evidence for parietal and prefrontal mechanisms. Journal of Cognitive Neuroscience, 12 (Suppl. 2), 130–144. Mayer, E., Martory, M. D., Pegna, A. J., Landis, T., Delavelle, J., & Annoni, J. M. (2000). A pure case of Gerstmann syndrome with a subangular lesion. Brain, 122, 1107–1120. McCloskey, M. (1992). Cognitive mechanisms in numerical processing: Evidence from acquired dyscalculia. Cognition, 44, 107–157. McCloskey, M., Aliminosa, D., & Sokol, S. M. (1991). Facts, rules, and procedures in normal calculation: Evidence from multiple single-patient studies of impaired arithmetic fact retrieval. Brain and Cognition, 17, 154–203. McCloskey, M., & Caramazza, A. (1987). Cognitive mechanisms in normal and impaired number processing. In G. Deloche & X. Seron (Eds.), Mathematical disabilities: A cognitive neuropsychological perspective (pp. 201–219). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. McCloskey, M., Caramazza, A., & Basili, A. (1985). Cognitive mechanisms in number processing and calculation: Evidence from dyscalculia. Brain and Cognition, 4, 171–196. McCloskey, M., Sokol, S. M., & Goodman, R. A. (1986). Cognitive processes in verbal-number production: Inferences from the performance of brain-damaged subjects. Journal of Experimental Psychology: General, 115, 307–330. McCloskey, M., Sokol, S. M., Goodman-Shuman, R. A., & Caramazza, A. (1990). Cognitive representations and processes in number production: Evidence from cases of acquired dyscalculia. In A. Caramazza (Ed.), Advances in cognitive neuropsychology and neurolinguistics (pp. 1–32). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.

226

Seron

McNeil, J., & Warrington, E. (1994). A dissociation between addition and substraction with written calculation. Neuropsychologia, 32, 717–724. Meck, W. H., & Church, R. M. (1983). A mode control model of counting and timing processes. Journal of Experimental Psychology: Animal Behavior Processes, 9, 320–334. Moyer, R. S., & Landauer, T. K. (1967). Time required for judgements of numerical inequality. Nature, 215, 1519–1520. Naccache, L., & Dehaene, S. (2001). The priming method: Imaging unconscious repetition priming reveals an abstract representation of number in the parietal lobes. Cerebral Cortex, 11, 966–974. Noël, M. P., & Seron, X. (1993). Arabic number reading deficit: A single case study. Cognitive Neuropsychology, 10, 317–339. Noël, M. P., & Seron, X. (1995). Lexicalization errors in writing arabic numerals: A single case study. Brain and Cognition, 29, 151–179. Pebenito, R. (1987). Developmental Gerstmann syndrome: Case report and review of the literature. Developmental and Behavioral Pediatrics, 8, 229–232. Pesenti, M., Seron, X., & Van der Linden, M. (1994). Selective impairment as an evidence for mental organisation of arithmetical facts: BB, a case of preserved subtraction? Cortex, 30, 661–671. Pesenti, M., Thioux, M., Seron, X., & de Volder, A. (2000). Neuroanatomical substrates of arabic number processing, numerical comparison, and simple addition: A PET study. Journal of Cognitive Neuroscience, 12, 461–479. Piazza, M. (2004). Processus de quantification: subitizing, dénombrement et estimation de numérosités (ch. 5). In M. Pesenti & X. Seron (Eds.), La Cognition numérique (pp. 113–134). Paris: Hermes Science, Lavoisier. Pinel, P., Dehaene, S., Rivière, D., & Le Bihan, D. (2001). Modulation of parietal activation by semantic distance in a number comparison task. NeuroImage, 14, 1013–1026. Pinel, P., Le Clec’H, G., van de Moortele, P.-F., Naccache, L., Le Bihan, D., & Dehaene, S. (1999). Event-related fMRI analysis of the cerebral circuit for number comparison. Neuroreport, 10, 1473–1479. Poltrock, S. E., & Schwartz, D. R. (1984). Comparative judgments of multidigit numbers. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 32–45. Power, R. J. D., & Dal Martello, M. F. (1990). The dictation of Italian numerals. Language and Cognitive Processes, 5, 237–254. Power, R. J. D., & Longuet-Higgins, F. R. S. (1978). Learning to count: A computational model of language acquisition. Proceedings of the Royal Society of London. Series B., 200, 391–417. Rickard, T. C., Romero, S. G., Basso, G., Wharton, C. M., Flitman, S., & Grafman, J. (2000). The calculating brain: An fMRI study. Neuropsychologia, 38, 325–335. Rourke, B. P. (1993). Arithmetic disabilities, specific and otherwise: A neuropsychological perspective. Journal of Learning Disabilities, 26, 214–226. Seron, X., & Deloche, G. (1983). From 4 to four: A supplement to “From three to 3”. Brain, 106, 735–744. Seron, X., & Deloche, G. (1984). From 2 to two: An analysis of a transcoding process by means of neuropsychological evidence. Journal of Psycholinguistic Research, 13, 215–235. Seron, X., & Noël, M. P. (1995). Transcoding numbers from the Arabic code to

12. The neuropsychology of calculation

227

the verbal one or vice versa: How many routes? Mathematical Cognition, 1, 215–235. Seron, X., Deloche, G., & Cornet, J. A. (1991). Dots counting by brain damaged subjects. Brain and Cognition, 17, 116–137. Simon, T. J. (1997). Reconceptualizing the origins of number knowledge: A nonnumerical account. Cognitive Development, 12, 349–372. Simon, T. J. (1999). The foundation of numerical thinking in a brain without numbers. Trends in Cognitive Sciences, 3, 363–365. Singer, H. D., & Low, A. A. (1933). Acalculia. Archives of Neurology and Psychiatry, 29, 467–498. Sokol, S. M., McCloskey, M., Cohen, N. J., & Aliminosa, D. (1991). Cognitive representations and processes in arithmetic: Inferences from the performance of braindamaged subjects. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17, 355–376. Spelke, E. S., & Tsivkin, S. (2001). Language and number: A bilingual training study. Cognition, 78, 45–88. Stanescu-Cosson, R., Pinel, P., Van de Moortele, P. F., Le Bihan, D., Cohen, L., & Dehaene, S. (2000). Understanding dissociations in dyscalculia—a brain imaging study of the impact of number size on the cerebral networks for exact and approximate calculation. Brain, 123, 2240–2255. Starkey, P. (1992). The early development of numerical reasoning. Cognition, 43, 93–126. Starkey, P., & Cooper, R. G. (1980). Perception of numbers by human infants. Science, 210, 1033–1034. Stein, I. (1992). The representation of egocentric space in the posterior parietal cortex. Behaviour and Brain Sciences, 15, 691–700. Strauss, A., & Werner, H. (1938). Deficiency in the finger schema in relation to arithmetic disability (finger agnosia and acalculia). American Journal of Orthopsychiatry, 8, 719–725. Strauss, M. S., & Curtis, L. E. (1981). Infant perception of numerosity. Child Development, 52, 1146–1152. Tegnér, R., & Nybäck, H. (1990). “Two hundred and twenty 4our”: A study of transcoding in dementia. Acta Neurologica Scandinavica, 81, 177–178. Thioux, M., Ivanoiu, A., Turconi, E., & Seron, X. (1999). Intrusions of the verbal code during the production of Arabic numerals: A single case study in a patient with probable Alzheimer’s disease. Cognitive Neuropsychology, 16, 749–773. Van Harskamp, N. J., & Cipolotti, L. (2001). Selective impairment for addition, subtraction and multiplication. Implications for the organization of arithmetical facts. Cortex, 37, 363–388. Van Harskamp, N. J., Rudge, P., & Cipolotti, L. (2002). Are multiplication facts implemented by the left supramarginal and angular gyri? Neuropsychologia, 40, 1786–1793. Verguts, T., & Fias, W. (2004). Representation of number in animals and humans: A neural model. Journal of Cognitive Neuroscience, 16, 1493–1504. Walsh, V. (2003). Cognitive neuroscience: Numerate neurons. Current Biology, 13, 447–448. Warrington, E. K. (1982). The fractionation of arithmetical skills: A single case study. Quarterly Journal of Experimental Psychology, 34A, 31–51. Warrington, E. K., & James, M. (1967). Tachistoscopic number estimation in patients

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Seron

with unilateral cerebral lesions. Journal of Neurology, Neurosurgery, and Psychiatry, 30, 468–474. Whalen, J., Gallistel, C. R., & Gelman, R. (1999). Nonverbal counting in humans: The psychophysics of number representation. Psychological Science, 10, 130–137. Whalen, J., McCloskey, M., Lindemann, M., & Bouton, G. (2002). Representing arithmetic table facts in memory: Evidence from acquired impairments. Cognitive Neuropsychology, 19, 506–522. Wiese, H. (2003). Numbers, language and the human mind. Cambridge: Cambridge University Press. Wynn, K. (1992). Addition and subtraction by human infants. Nature, 358, 749–750. Zago, L., & Pesenti, M. (2004). Bases neurales des activités numériques. In M. Pesenti & X. Seron (Eds.), La Cognition numérique (pp. 249–278). Paris: Hermes Science, Lavoisier. Zago, L., Pesenti, M., Mellet, E., Crivello, F., Mazoyer, B., & Tzourio-Mazoyer, N. (2001). Neural correlates of simple and complex mental calculation. NeuroImage, 13, 314–327.

SECTION IV

Modality-specific recognition disorders

13 Perceptual categorization Language and thought Jules Davidoff

History Vignolo (1999) pointed out that the inability to carry out tasks requiring categorization is a common consequence of aphasia and is crucial to the debate concerning the relationship between impaired language and thought. On that issue, different opinions were strongly expressed in the early days of modern neuropsychological research. Wernicke (1874), for example, considered aphasia a lexical impairment. Contrary to Wernicke, Hughlings Jackson (1879; see Zangwill, 1964), famously declared that aphasic patients are “lame in thinking”. The argument between the two opposing views was considered one of the most crucial in neuropsychology and surfaced many times in the subsequent 100 years (Geschwind, 1974; Goldstein, 1948; Head, 1926; Marie, 1906). Yet, there would not be a large corpus of evidence if one were to search only through current investigations. The cyclical nature of investigations in science is well known, and, at present, the cycle concerning the effects of aphasia on categorization is at a low point. From Vignolo’s chapter (1999) in the Handbook of Clinical and Experimental Neuropsychology, one could give an estimate of around 20–30 years between high points of activity. The present stage of the cycle probably explains why so little of the previous research on categorization is included in current neuropsychological texts (Ellis & Young, 1996; Shallice, 1988). On the view that related aphasia to conceptual impairment, the two disorders have been variously seen to derive from a more general impairment in the use of symbols (Finkelburg, 1870; see Vignolo, 1999), or from impaired abstraction and categorization capacity (Goldstein, 1948; Teuber & Weinstein, 1956). It was Goldstein (1948) in particular who considered that a loss of abstract processing could explain impairments in all categorization tasks (Noppeney & Wallesch, 2000). Goldstein (1948) remarked on the particular difficulty that patients with amnesic (anomic) aphasia show when categorization requires the ability to think abstractly. Similar categorization tasks to those employed by Goldstein were used in a few studies in the last major revival of interest in the issue in the 1970s and early 1980s. For example, De Renzi, Faglioli, Scotti, and Spinnler (1972)

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asked patients to sort skeins of coloured wool in the classical Holmgren Test. However, they could only conclude that the “reason for aphasics’ poor performance is not clear” (p. 147). Impaired categorization was also restricted to anomic aphasia by Caramazza and colleagues (Caramazza, Berndt, & Brownell, 1982; Whitehouse, Caramazza, & Zurif, 1978). While patients with Broca’s aphasia had no difficulty with a categorization task, those with anomic aphasia were substantially impaired (Whitehouse et al., 1978). Similarly, in the task of discriminating between a cup and a bowl (Labov, 1973), Caramazza et al. (1982) found that patients with anomic aphasia were impaired and relied on the crude visual similarity of the presence or absence of a handle to make categorical judgements. Caramazza et al. (1982) commented that “the strongest statement that can be made at this time is that the type of semantically based deficit we have uncovered appears to be associated with some types of posterior pathology, but not with all posterior lesions” (p. 186).

Current revival: the patient LEW The current revival of interest in the relationship between language and thought in anomic aphasia comes from the work of Davidoff and colleagues in their studies on the patient LEW (Davidoff & Roberson, 2004; Roberson, Davidoff, & Braisby, 1999). LEW had a stroke that left him with a moderate right-sided motor weakness. LEW is severely anomic and this is particularly marked in his naming to visually presented stimuli (Druks & Shallice, 2000) (Figure 13.1). In his more recent assessment (Davidoff & Roberson, 2004), LEW was given the full set of objects (nouns) and verbs from Druks and Masterson (2000). For nouns, he scored 47/162 correct and verbs 17/100 correct (Figure 13.1) with no evidence of any predictive value of frequency, familiarity, age-of-acquisition, imageability, or visual complexity in analyses of correct and incorrect noun items. Errors were, as in Druks and Shallice

Figure 13.1 LEW’s naming and comprehension. From Davidoff & Roberson (2004); Druks & Shallice (2000).

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(2000), for nouns, attempts at circumlocutions, attempts to gesture, and occasional semantic errors; for verbs, there were mostly omissions. However, his comprehension was much better. On the spoken presentation of the word/ picture-matching task of the Psycholinguistic Assessment of Language Processing in Aphasia (PALPA) (Kay, Lesser, & Coltheart, 1992), he scored 33/40 when examined by Druks and Shallice (2000); on retesting, his performance was very similar; he scored 35/40 at the beginning of testing and 37/40 when retested a year later (Davidoff & Roberson, 2004) (Figure 13.1). LEW was unable to name or reliably point to colours, and this prompted an investigation of his ability to sort by colour. Goldstein (1948) noted that patients with anomic aphasia had particular difficulty in sorting colours. Moreover, he reported that patients had distinctive approaches to performing such tasks. They would pick a colour and try to find one identical to it. If the display contained no identical colours, then the colour was reluctantly placed next to one that was very similar; this was repeated for the whole display giving many pairs of colours. An alternative approach was to declare that all the colours belonged to the same group. Thus, the colours were either all the same or all different. Goldstein summarized his patients as having lost an abstract attitude. They, for example, did not put the categorized items into piles but rather required them all to be visible; Goldstein interpreted this behaviour as an indication that the categorization was not being driven by an abstract concept. With only a concrete attitude to the stimuli, an individual colour is not seen as representative of a class of colours and cannot be put into a group. Goldstein noted that the concrete attitude adopted by the patients could be seen by their unwillingness, when sorting, to put colours on top of each other. Not being driven by an idea of “redness”, “blueness”, etc., the patient can assign groups only by perceptual similarity, and for this it is necessary to see the stimuli. LEW’s approach to sorting colours was very similar to that recorded by Goldstein (Roberson et al., 1999). LEW’s inclination to sort by perceptual rather than categorical similarity was further assessed in a recent examination. He was given a task in which he had to point to the odd-one-out from three stimuli drawn from all possibilities (n = 120) of 10 different colours. The 10 colours (set 1) all had the same lightness and saturation. The colours were two pinks, three greens, two blues, one orange, one brown, and one purple. Another set of 10 stimuli (set 2) was chosen so that the colours with more than one example in each category were as perceptually distinct from each other as possible while still reliably given the same name (blue, green, etc.). It is possible to work out the solution for each triad by perceptual similarity from the trichromatic coordinates of each colour (Wyszecki & Stiles, 1982). For our purposes, a choice was considered to be an error if it was different from the solution based on perceptual distance. We examined the numbers of errors made by LEW and eight controls. The calculation of perceptual distance is not an easy matter by observation alone,

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and, as for many triads there was not an obvious answer; errors were predicted for both LEW and controls. However, for the second set of stimuli in particular, there would also be errors from making judgements based on category similarity. For some triads, the two stimuli that were from the same category (e.g. blue) were not perceptually the closest. If performance was based on category similarity, there would be an increase in errors. It was argued that LEW would be less influenced by the effect of category than controls. The prediction was confirmed. For set 1, LEW made 38 errors compared to 34.9 for controls (sd = 4.45) errors (z = .70, p > .05). For set 2, LEW made 32 errors compared to 66.0 for controls (sd = 8.45) errors (z = 4.02, p < .001). LEW was also unable to categorize shapes (Davidoff & Roberson, 2004) and facial expressions from stimuli where one expression was morphed into another (Roberson et al., 1999). Again, LEW was bewildered by the tasks. For example, in sorting circles, squares, and triangles, he picked up one of the circles and found a few of the other circles that he considered should go with it. He then declared that all the rest (circles, squares, and triangles) should be considered another group. Are these problems part of a more general intellectual decline as suggested by the phrase “lame in thinking”? In answering this question, there is a problem in that LEW has considerable difficulty in reading and writing; so, many standard intelligence tests would be inappropriate. However, Druks and Shallice (2000) reported his verbal IQ as 71 and his performance IQ as 83. More recently, he was given three subtests from the Vespar (Langdon & Warrington, 1995). His scaled scores were verbal odd one out = 8, spatial odd one out = 11, and spatial analogy = 8. These scores were not different from what might be expected from someone, like LEW, who left school at 14 and found employment as a bailiff (rent collector). His performance on the WAIS Matrices was 13/32, putting him at percentile 43. An example of the level at which he can succeed is given in Figure 13.2. Thus, standard intelligence testing gives no reason to believe that his impaired sorting is part of a more general intellectual decline. We also investigated LEW’s ability in analogical reasoning because Rattermann and Gentner (1998) argued that relational labels invite children to notice patterns and hence to make comparisons. They found that young children have greater difficulty in making choices based on relational size (such as the smallest item in a set) with “rich” objects (varying in many dimensions, including size) than with “sparse” objects (varying only in size). Young children (3 and 4 years old) were unable to resist matching by overall object similarity, rather than relational size. Not until 5 years of age were children able to overcome the temptation to match objects, and to choose by relational similarity. However, younger children made more relational choices when prompted with the labels “big”, “little”, “tiny” or “mommy”, “daddy”, and “baby”. Thus, hearing common labels could embark children on a comparison that helps promote abstract thought. The age at which analogical reasoning develops is greater than that currently found for the acquisition of colour labels (Davidoff, 1991; Rattermann & Gentner, 1998). So, it might be a

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Figure 13.2 Example of the non-verbal reasoning task at which LEW can succeed. LEW has to choose which of the five alternatives should go into the place marked with a ?

reasonable assumption that, as LEW cannot make use of colour labels, he would also not be able to make use of relational labels. Davidoff and Roberson (2004) gave LEW a close version of the tasks as used by Rattermann and Gentner (1998). In their task, the experimenter and child were presented with cards containing three objects of increasing size. The cards differed only in one respect. For the child, the objects were decreased in size so that the middle object had the same size as the smallest object, and the largest the same size as the middle object, etc. There were both rich and sparse object sets. Rich stimulus sets contained three objects that varied along multiple dimensions, including size, within the two sets (e.g. a large black hat, a medium-sized red rose, and a small white door). Sparse stimulus sets contained three simple sparse objects that were identical in all respects except size within the two sets (e.g. patterned squares). The experimenter and LEW sat opposite to each other and the experimenter explained, “I’m going to point to one of the three things on my card while you watch me. If you think about the thing I’m pointing to, you’ll be able to guess which the equivalent one in your set is.” If LEW were to use a relational rule to make his decision, when the experimenter pointed to the middle object in her set, LEW should also choose the middle object.

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However, if LEW’s decisions were based on overall similarity, then he would choose the smallest object. Feedback was either “yes, that’s the one” or “no, I was thinking of another one”. There were 12 trials for each set of stimuli. LEW completed all 24 trials on four different occasions. On separate occasions, LEW was given “family” labels for the stimuli. Following Rattermann and Gentner (1998), the experimenter used the labels “daddy”, “mummy”, and “baby” to label the large, medium, and small stimuli. On further subsequent occasions, LEW was tested with the “size” labels: “big”, “middlesized”, and “small”. Figure 13.3 shows results for LEW for sparse and rich stimuli with and without labels compared to those made by 3-, 4-, and 5-year-olds in Rattermann and Gentner (1998). LEW performed above chance in all conditions. In the no-label condition, his scores resembled those of 4- and 5year-old children. LEW did not show the same pattern of improvement that Rattermann and Gentner (1998) found for 3-year-olds when prompted with family labels. LEW seemed confused by the labels “daddy”, “mummy”, and “baby” in that these resulted in decreased (albeit not reliably) performance. However, with size labels, LEW’s performance improved in both conditions. For the sparse condition, ceiling effects prevented a significant improvement, but not for the rich condition. Errors were always to the identical object for the rich condition; this was also the predominant error in the sparse condition. Rattermann and Gentner (1998) suggested that children succeed with plain stimuli because they have some understanding of the relative size of objects, but fail on the complex set because the object identity match

Figure 13.3 LEW’s performance on the analogical reasoning tasks taken from Rattermann and Gentner (1998) with no labels and with family or size labels. Asterisks indicate significant increase in performance from the no-label condition.

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overrides the relative size match. The same explanation could well hold for LEW. From these data, it can be seen that LEW was able to reason analogically at least to the ability of a 4/5-year-old child and did not make all judgements on the basis of perceptual similarity between objects. Indeed, LEW showed evidence of analogical reasoning even with randomly arranged stimuli, he did not do any worse with abstract rather than with real-life stimuli, and he improved on the tasks with the assistance of (some) labels (Davidoff & Roberson, 2004). However, like children, his analogical reasoning could be confused by complex stimuli and distracted by object similarity. Yet, there is no doubt that a 4/5-year-old child can sort colours. Gentner has argued that language plays a critical part in acquiring rules, but it is unclear whether that should be a necessary part or rather that language directs the child’s attention to the critical aspects of the similarity judgement. LEW achieved analogical similarity judgements without being able to perform perceptual categorizations. Thus, there is an argument for believing the two types of thought are different in kind and that the linguistic abilities required for analogical reasoning are not those required for taxonomic classification.

Thematic versus taxonomic relationships LEW was not generally intellectually impaired, so what was the origin of his inability to sort colours? Semenza (1999) has argued that the impairment in anomic aphasia is better understood as a difficulty with conceptual (taxonomic) as opposed to thematic relationships (see from the last cycle, Bisiacchi, Denes, & Semenza, 1976; Gardner & Zurif, 1976; Melice-Ledent, Gainotti, Messerli, & Tissot, 1976; Semenza, Denes, Lucchese, & Bisiacchi, 1980). Thus, LEW was given a task that taps the distinction between rulebased (taxonomic) and associative (thematic) learning systems (Sloman, 1996). Rule-based systems operate on symbolic structures, whereas associative systems reflect the similarity structure of acquired knowledge and relations of temporal and spatial contiguity. The task was based on experiments 1–3 of Markman and Hutchinson (1984). Twenty-two triads were constructed of three coloured photographs of common objects arranged to form a triangle. A standard object (e.g. police car, tennis shoe) was placed at the top of the triangle, and a taxonomic choice (e.g. saloon car, high-heeled shoe) or thematic choice (e.g. policeman, foot) was placed at the two lower apices. LEW, as for the children tested by Markman and Hutchinson, was asked to point to another one that was the same as the standard object. For these simple tasks, adults always make taxonomic choices, but young children do not. LEW approached the task like the 4-year-olds in Markman and Hutchinson. Clearly, LEW had at least a pronounced bias to approach these tasks by association. However, there is an alternative explanation. In the last cycle, an alternative to the taxonomic versus thematic distinction was proposed by the Konstanz group (Cohen, Engel, Kelter, List, & Strohner,

238 Davidoff 1976; Cohen, Kelter, and Woll, 1980; review in Vignolo, 1999; Kelter, Cohen, Engel, List, & Strohner, 1976). Their alternative represents a quite different kind of explanation and implies the loss of a type of knowledge rather than of a type of thought. In their tasks, similar in design to those of Markman and Hutchinson (1984) and those used in the Pyramids and Palm Trees Test (Howard & Patterson, 1992), the patient has to decide which two out of three pictures go together. They found that aphasic patients were considerably more impaired if the connection was “perceptual” rather than “situational”. For example, aphasic patients failed to connect that a snowman should go with a swan because both are white but succeeded in a task that required putting together a guitar and a bull because both are connected with Spain. Thus, the Konstanz group made, from many studies, the conclusion that it is visual knowledge about objects that is impaired in aphasia. In doing so, they attributed the impairment to a loss of knowledge concerning the visual attributes of objects. LEW was given odd-one-out tasks, similar to those used by the Konstanz group, in a paradigm taken from Hillis and Caramazza (1995). LEW was asked, from both words and line drawings, which was the odd-one-out in three tasks: colour, size, and function. He showed no evidence that he could judge which object of the triad had a different colour from the other two (Figure 13.4) and was accordingly worse than young and old (agematched) controls. The dramatic difference between the tasks was independent of the form (line drawings or words) of presentation (see Hart & Gordon (1990) for a similar finding in a similar task). There was a similar but less dramatic pattern of performance for the size judgements. The pattern for function judgements was different. LEW did not differ from controls in judging line drawings; he was somewhat impaired on function judgements from words, but not to the same extent as for colour and size judgements. LEW’s performance on the colour odd-one-out task does not simply derive from loss of knowledge. He could recognize a picture that was wrongly coloured (Davidoff & Roberson, 2004). Apparently, it is rather the type of question that can produce apparent failure. In that, he resembles the patients described by Beauvois and Saillant (1985), and it is worth pointing out the similarities but also the important differences. Beauvois and Saillant (1985) showed that optic aphasics might demonstrate little ability to retrieve objectcolour knowledge in the tasks used by De Renzi and Spinnler (1967); yet, they could be made to show normal performance with other procedures. The particular procedures used by Beauvois and Saillant to show normal performance concerned the inhibition of verbal associations. When their patients were allowed to use their visual imagery uncontaminated by verbal associations, they showed excellent retrieval for object-colour. Beauvois and Saillant (1985) argued that their cases were examples of optic aphasia caused by a visual–verbal disconnection. LEW certainly does not fit the normal pattern of an optic aphasic (Druks & Shallice, 2000), not least because his

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Figure 13.4 LEW’s performance on three odd-one-out tasks with both pictures and words. Latencies at bottom are from young controls and show that the three tasks are matched for speed as well as accuracy. From Davidoff & Roberson (2004); after Hillis & Caramazza (1995).

performance on the odd-one-out task was equivalent in pictures and words. However, the principal difference from the cases of Beauvois and Saillant (1985) is that LEW was not failing at object-colour retrieval but at the taxonomic classification of colour. Considering the function odd-one-out tasks, there are two interpretations of LEW’s preserved performance. The first is that perceptual and functional aspects of knowledge might be both modularly represented and therefore can be selectively impaired (Warrington, 1975; Warrington & Shallice, 1984). An alternative interpretation is that his thinking is based on associations (thematic) and this ability can solve apparently taxonomic tasks. In another

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task, LEW was asked to divide animals into British and foreign (Roberson et al., 1999), and he did this accurately and rapidly. LEW was asked how he did the task. His answer was “zoo”. If, by “zoo”, he meant that these animals were found in a zoo, his thought process was of an associative type. LEW would also go wrong in a few object-categorization tasks by basing his classification on his personal knowledge. He, for example, put a shirt with chest of drawers presumably based on where it would be kept in his house. Whether or not all function odd-one-out tasks can be solved by LEW by association remains to be resolved. Certainly, he could not solve odd-oneout tasks of colour and size in the same way, as these are not associations but object attributes. To solve those tasks, he would need to retrieve the verbal knowledge that a camel or bear is brown or name the colour in a visual image. It is doubtful that such perceptual knowledge is stored verbally, but we also know that he cannot name those colours. So, he could not name the colours in an image. In the Goldstein framework, he would need to understand that different-coloured exemplars were in the same taxonomy.

Implications for perceptual categorization LEW’s profile of preserved and impaired function casts light on four important and related issues for perceptual categorization. The first of these concerns a debate about different types of thought processes (Fodor, 1998a; Gentner & Medina, 1998), the second concerns the different representations for concrete and abstract nouns, the third is the role of preserved naming in perceptual classification, and the fourth concerns the type of patient who would show similar disorders of perceptual classification. Turning to the first of these issues, Fodor (1998a, 1998b) has argued that concepts—of the taxonomic kind—cannot be derived empirically. In contrast, and in support of an empiricist position, Gentner and colleagues have shown that similarity judgements can be affected by object similarity; hence, they argue that similarity may bootstrap the acquisition of rule-based skills. LEW was susceptible to the same distractions as are children in his analogical reasoning; nevertheless, like children, he was also somewhat immune to them. The important point is that children at the same level of analogical reasoning as LEW perform very much better at taxonomic tasks. Thus, LEW showed that the ability to make taxonomic classifications does not depend on the ability to reason analogically. In the contrast between concrete and abstract nouns, abstract nouns are essentially of the taxonomic type and concrete nouns essentially thematic, although the distinctions are not always straightforward. Consider, for example, an apple. The abstract (taxonomic) classification of an apple would be “fruit”. The concrete (thematic) classification of an apple could relate it to another object (such as tree). However, two types of fruit (apple and banana) might be classified together by virtue of their being seen together, just as

13. Perceptual categorization 241 LEW classified animals as foreign because they are in the zoo. Indeed, he may well have made relatively few errors (see Davidoff & Roberson, 2004) on the Pyramids and Palm Trees Test (Howard & Patterson, 1992) because an apparently taxonomic decision can, in fact, be based on a thematic decision. A similar complexity can arise for thematic classification. The fact that an apple is red might be considered a concrete property of an apple. Nevertheless, if the decision to classify an apple is based on redness, it is a taxonomic decision and one that LEW failed abysmally. The best neuropsychological evidence for distinctly separable concrete and abstract representations is that they are known to double-dissociate in naming studies. Aphasic patients, in general, show a concreteness advantage in word retrieval (Goodglass, Hyde, & Blumstein, 1969), but this not always the case (Breedin, Saffran, & Coslett, 1994; Goldstein, 1948; Sirigu, Duhamel, & Poncet, 1991; Warrington, 1975; Warrington & Shallice, 1984). For example, Warrington’s patient could define an abstract word, such as supplication, as “making a serious request for help” but could give no definition for the word alligator. Their separation is also confirmed by a study in which there was a selective difficulty in retrieving abstract words without an impairment in comprehension (Franklin, Howard, & Patterson, 1995), thus ruling out damage to knowledge structures as causing impairment in abstract terms. Of course, abstract words are generally less common and longer, but these characteristics too have been shown to be insufficient to explain their difficulty for an anomic patient (Henaff Gonon, Bruckert, & Michel, 1989). The taxonomic difficulty will be seen especially for perceptual terms, such as colour, because these are essentially abstract. Colour, for example, only allows taxonomic classification. Turning to the third issue that is addressed by LEW’s pattern of performance, we can argue that language (that is, naming) is even more critical in classification than the role proposed for it by Gentner. The failure of LEW at perceptual categorization tasks is extremely important. Despite what might appear otherwise, the critical aspect of perceptual categorization is that it depends on language (see Dummett, 1975; Roberson et al., 1999). However, the relationship between naming and other categorization tasks is not straightforward (Hampton, 2001; Sloman, Malt, & Fridman, 2001). The complexity arises because of the many ways that objects may be categorized (determined to be similar). For some tasks, perceptual similarity may be the dominant procedure for categorization; for other tasks, it could be some functional or contextual similarity. The consequence is that there may be categorization tasks, including sorting, that for normal individuals are not affected by the names given to objects (Sloman, Malt, & Fridman, 2001). Yet, we know that the effects of name dominance can be striking after brain damage, allowing a patient to produce gestures or drawings that correspond to verbal mistakes rather than to the object presented (Beauvois, Saillant, Meininger, & Lhermitte, 1978; Davidoff & Wilson, 1985; Lhermitte & Beauvois, 1973; Ohtake, Fujii, Yamadori, Fujimori, Hyakawa, & Suzuki, 2001; Oxbury, Oxbury, &

242 Davidoff Humphrey, 1969). These effects are so dramatic as to suggest that it is not only memory codes that are altered by naming but also the processing of current visual stimuli. A similar claim has recently been made for perceptual categorization (Davidoff, 2001). We therefore consider LEW’s deficits in the context of his loss of naming. The naming of objects in aphasia is multidetermined, and there are many contributing factors to an inability to name objects. One of these factors is impairment resulting from damage to semantics or features of object knowledge (Hillis, 2001; Katz & Fodor, 1963). Semantic errors in comprehension are generally associated with semantic impairments in naming (Gainotti, Miceli, Caltagorone, Silveri, & Massulo, 1981), but Butterworth, Howard, and McLoughlin (1984) caution against making a direct link between the two disorders. LEW does not make a substantial number of semantic errors. Thus, semantic errors are not the major cause of LEW’s naming disorder. Impaired semantics also cannot be the reason that LEW prefers to make thematic decisions in categorization tasks. Semantic errors in comprehension and naming may accompany preserved thematic associations (Howard & Orchard-Lisle, 1984), but this is not the case for LEW. For him, there is a limited ability to name objects but when given a description of an object’s features and functions, his naming showed some improvement (Druks & Shallice, 2000), suggesting that LEW’s impairment does not stem from a weakened knowledge base. We argue that LEW’s critical impairment was his anomia, but he lost more than just the names. He, like other patients with colour anomia (Davidoff, 1991; Davidoff & Ostergaard, 1984), also could not point correctly to a named colour or benefit from a colour label. LEW’s loss, as Goldstein put it, is that of an abstract attitude that makes him unable consciously to allocate items to perceptual categories. Hence, his impairment refers not to a type of knowledge store but to a type of thought. A disorder that prevents naming would at the very least promote associative (thematic) rather than taxonomic procedures for categorization. One reason would be the general inclination to solve categorization tasks verbally (Ashby, Alfonso-Reese, Turken, & Waldron, 1998), and this would be particularly the case for complex multidimensional stimuli. However, it is not the case that LEW’s categorization difficulties were only present for complex stimuli. LEW had also difficulties in categorizing even the simplest perceptual stimuli. For these stimuli, observation by itself is insufficient to arrive at a categorical solution (Anderson & Fincham, 1996; Dummett, 1975), and therein lies LEW’s difficulty. For such classifications, the concept and the name are, in effect, the same thing, and LEW is without names to assist the categorical solution. Where patients such as LEW can name, they can categorize. In an odd-one-out task in which LEW can successfully name each item, he would succeed in categorization just as he could succeed when given names in the Markman task. With respect to the fourth issue, clearly related to the third issue, concerning the types of patient that would exhibit similar disorders, it might be first

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noted they ought not to be rare. Disorders of taxonomic classification should be common because naming disorders are common. They may appear less common than they are because so many sorting tasks are soluble by thematic associations. It is only for perceptual categorizations that the taxonomic failure becomes vivid, because, for those tasks, there is no other way to the solution. However, before restricting a taxonomic impairment to a naming disorder, it is necessary to rule out other likely candidate populations that might be argued to show the same sort of deficit. The type of aphasic patient that would show disorders of taxonomic classification has to be one in which language impairment is central. One would not expect impairments of perceptual categorization where there is merely a problem in production. Indeed, previous research on the impaired perceptual categorization abilities of aphasic patients has eliminated those patients with more anterior damage (Caramazza et al., 1982; De Renzi et al., 1972). So, the least likely candidate patients are those whose problems involve the syntactic elements of language however essential they are in linguistic theory. Impaired sentence comprehension is demonstrable in patients with good word comprehension (Caramazza & Zurif, 1976; von Stockert & Bader, 1976), and preserved syntax coexists with naming impairments (Hodges, Patterson, & Tyler, 1994). Furthermore, Varley, Siegel, and Want (2001) have shown that severe grammatical impairment does not preclude many abstract reasoning tasks such as theory of mind or playing chess. The locus of lesion critical for taxonomic classification is the left posterior cortex (Caramazza et al., 1982). Yet, such lesions may also result in degraded or inaccessible knowledge stores (Warrington, 1975), a disorder often referred to as semantic dementia (Snowden, Goulding, & Neary, 1989). Such patients often demonstrate loss of naming and, indeed, difficulty with taxonomic as opposed to thematic relationships (Semenza et al., 1980). However, the generally intact knowledge store of LEW (Druks & Shallice, 2000) does not prevent him making taxonomic errors; clearly, the disorders must be different. The same conclusion was drawn by Franklin, Howard, and Patterson (1995) in considering the selective impairment of the production of abstract words. In summary, we suggest that there are two types of categorization procedures (taxonomic and thematic) that have separable mental representations. In attempting to distinguish the two types and understand the processes underlying categorization, the major problem is that classification (family resemblance) of objects (animals, tools, etc.) could be obtained from visual similarity, by common habitat or size, or a myriad of other associations. It could even be argued that these associations are what constitute the category. The central thesis that derives from work on impaired perceptual categorization is not concerned to demonstrate problems with these thematic types of category. Aphasic patients may turn out to be over- or under-inclusive in the features of objects that, for them, define a category (Grossman, 1978, 1981) or be completely normal except for difficulties derived from word retrieval

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(Hough, 1993). The thesis is that there is a type of classification, independent of feature classification, unavailable to aphasics with naming disorders. One is, therefore, driven to the view that applying a name to a class of objects is a theoretically different ability from associating features in object knowledge, although, here, Goldstein (1948) warned of difficulties of interpretation if the naming is by rote (in his term, “pseudonaming”), rather than reflecting an abstract attitude. The critical impairment for LEW is argued to be his anomia, but he has lost more than just the names. LEW’s loss, as Goldstein put it, is that of an abstract attitude. LEW’s impairment makes him unable consciously to allocate items to perceptual categories. Hence, his impairment refers not to a type of knowledge store but to a type of thought.

References Anderson, J. R., & Fincham, J. M. (1996). Categorization and sensitivity to correlation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 259–277. Ashby, F. G., Alfonso-Reese, L. A., Turken, A. U., & Waldron, E. M. (1998). A neuropsychological theory of multiple systems in category learning. Psychological Review, 105, 442–481. Beauvois, M. F., & Saillant, B. (1985). Optic aphasia for colours and colour agnosia: A distinction between visual and visuo-verbal impairments in the processing of colours. Cognitive Neuropsychology, 2, 1–48. Beauvois, M. F., Saillant, B., Meininger, V., & Lhermitte, F. (1978). Bilateral tactile aphasia: A tacto-verbal dysfunction. Brain, 101, 381–401. Bisiacchi, P., Denes, G., & Semenza, C. (1976). Semantic fields in aphasia: An experimental investigation on comprehension of the relation of class and property. Archives Suisse de Neurologie, Neurochirurgerie et Psychiatrie, 118, 207– 213. Breedin, S. D., Saffran, E. M., & Coslett, B. (1994). Reversal of the concreteness effect in a patient with semantic dementia. Cognitive Neuropsychology, 11, 617–660. Butterworth, B., Howard, D., & McLoughlin, P. (1984). The semantic deficit in aphasia: The relationship between semantic errors in auditory comprehension and picture naming. Neuropsychologia, 22, 409–426. Caramazza, A., Berndt, R. S., & Brownell, H. H. (1982). The semantic deficit hypothesis: Perceptual parsing and object classification by aphasic patients. Brain and Language, 15, 161–189. Caramazza, A., & Zurif, E. (1976). Dissociation of algorithmic and heuristic processes in language comprehension: Evidence from aphasia. Brain and Language, 3, 572–582. Cohen, R., Engel, D., Kelter, S., List, G., & Strohner, H. (1976). Restricted association in aphasics and schizophrenics. Archiv für Psychiatrie und Nervenkrankheiten, 222, 325–338. Cohen, R., Kelter, S., & Woll, G. (1980). Analytical competence and language impairment in aphasia. Brain and Language, 10, 341–347. Davidoff, J. (1991). Cognition through color. Cambridge, MA: MIT Press. Davidoff, J. (2001). Language and perceptual categories. Trends in Cognitive Science, 5, 382–387.

13. Perceptual categorization

245

Davidoff, J., & Ostergaard, A. L. (1984). Short term colour memory and colour anomia. Brain, 107, 415–431. Davidoff, J., & Roberson, D. (2004). Preserved thematic and impaired taxonomic categorisation: A case study. Language and Cognitive Processes, 19, 137–174. Davidoff, J., & Wilson, B. A. (1985). A case of visual associative agnosia showing a disorder of pre-semantic categorisation. Cortex, 21, 121–134. De Renzi, E., Faglioni, P., Scotti, G., & Spinnler, H. (1972). Impairment of color sorting behavior after hemispheric damage: An experimental study with the Holmgren Skein Test. Cortex, 8, 147–163. De Renzi, E., & Spinnler, H. (1967). Impaired performance on color tasks in patients with hemispheric damage. Cortex, 3, 194–217. Druks, J., & Masterson, J. (2000). An object and action naming battery. Hove: Psychology Press. Druks, J., & Shallice, T. (2000). Selective preservation of naming from description and the “restricted preverbal message”. Brain and Language, 72, 100–128. Dummett, M. (1975). Wang’s paradox. Synthese, 30, 301–324. Ellis, A. W., & Young, A. W. (1996). Human cognitive neuropsychology. Hove: Psychology Press. Fodor, J. (1998a). Concepts. Oxford: Oxford University Press. Fodor, J. (1998b). In critical condition. Cambridge, MA: MIT Press. Franklin, S., Howard, D., & Patterson, K. (1995). Abstract word anomia. Cognitive Neuropsychology, 12, 549–566. Gainotti, G., Miceli, G., Caltagirone, C., Silveri, M. C., & Masullo, C. (1981). The relationship between type of naming error and semantic-lexical discrimination in aphasic patients. Cortex, 17, 401–410. Gardner, H., & Zurif, E. B. (1976). Critical reading of words and phrases in aphasia. Brain and Language, 3, 173–190. Gentner, D., & Medina, J. (1998). Similarity and the development of rules. Cognition, 65, 263–297. Geschwind, N. (1974). Selective papers on language and the brain. Boston: D. Reidel. Goldstein, K. (1948). Language and language disturbances. New York: Grune and Stratton. Goodglass, H., Hyde, M. R., & Blumstein, J. (1969). Frequency, picturability and availability of nouns in aphasia. Cortex, 5, 104–119. Grossman, M. (1978). The game of the name. An examination of linguistic reference after brain damage. Brain and Language, 6, 112–119. Grossman, M. (1981). A bird is a bird is a bird: Making reference with and without superordinate categories. Brain and Language, 12, 313–331. Hampton, J. A. (2001). The role of similarity in natural categorization. In U. Hahn & M. Ramscar (Eds.), Similarity and categorization (pp. 13–28). Oxford: Oxford University Press. Hart, J., & Gordon, B. (1990). Delineation of single word semantic comprehension deficits in aphasia, with anatomic correlations. Annals of Neurology, 27, 226–231. Head, H. (1926). Aphasia and kindred disorders of speech (vols. 1–2). London: Cambridge University Press. Henaff Gonon, M. A., Bruckert, R., & Michel, F. (1989). Lexicalization in an anomic patient. Neuropsychologia, 27, 391–407. Hillis, A. E. (2001). The organization of the lexical system. In B. Rapp (Ed.), Handbook of cognitive neuropsychology (pp. 185–210). Hove: Psychology Press.

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Davidoff

Hillis, A. E., & Caramazza, A. (1995). Cognitive and neural mechanisms underlying visual and semantic processing: Implications from “optic aphasia”. Journal of Cognitive Neuroscience, 7, 457–478. Hodges, J. R., Patterson, K., & Tyler, L. K. (1994). Loss of semantic memory: Implications for the modularity of mind. Cognitive Neuropsychology, 11, 505–542. Hough, M. S. (1993). Categorization in aphasia: Access and organization of goalderived and common categories. Aphasiology, 7, 335–357. Howard, D., & Orchard-Lisle, V. M. (1984). On the origin of semantic errors in naming: Evidence from the case of a global aphasic. Cognitive Neuropsychology, 1, 163–190. Howard, D., & Patterson, K. E. (1992). The Pyramids and Palm Trees Test. Bury St Edmunds: Valley Test Company. Jackson, J. H. (1879). On affections of speech from disease of the brain. Brain, 1, 304–330. Katz, J. J., & Fodor, J. A. (1963). The structure of a semantic theory. Language, 39, 170–210. Kay, J., Lesser, R., & Coltheart, M. (1992). Psycholinguistic assessments of language processing in aphasia (PALPA). Hove: Lawrence Erlbaum Associates Ltd. Kelter, S., Cohen, R., Engel, D., List, G., & Strohner, H. (1976). Aphasic disorders in matching tasks involving conceptual analysis and covert naming. Cortex, 12, 383–394. Labov, W. (1973). The boundaries of words and their meanings. In C.-J. N. Bailey & R. W. Shuy (Eds.), New ways of analyzing variations in English. Washington, DC: Georgetown University Press. Langdon, D. W., & Warrington, E. K. (1995). Verbal and Spatial Reasoning Test (VESPAR). Hove: Psychology Press. Lhermitte, F., & Beauvois, M. F. (1973). A visual-speech disconnection syndrome. Report of a case with optic aphasia, agnostic alexia and agnosia. Brain, 96, 695–714. Marie, P. (1906). Révision de la question de l’aphasie: la troisième circonvolution frontale gauche ne joue aucun rôle spécial dans la fonction du langage. Semaine Médicale, 21, 241–247; 493–500; 565–571. Markman, E., & Hutchinson, J. (1984). Children’s sensitivity to constraints on word meaning: Taxonomic vs. thematic relations. Cognitive Psychology, 16, 1–27. Melice-Ledent, S., Gainotti, G. Messerli, P., & Tissot, R. (1976). Logique elementaire et champs semantiques dans l’aphasie. Revue Neurologique, 132, 343–359. Noppeney, U., & Wallesch, C. W. (2000). Language and cognition—Kurt Goldstein’s theory of semantics. Brain and Cognition, 44, 367–386. Ohtake, H., Fujii, T., Yamadori, A., Fujimori, M., Hyakawa, Y., & Suzuki, K. (2001). The influence of misnaming on object recognition: A case of multimodal agnosia. Cortex, 37, 175–186. Oxbury, J. M., Oxbury, S. M., & Humphrey, N. (1969). Varieties of colour anomia. Brain, 92, 847–860. Rattermann, M. J., & Gentner, D. (1998). The effect of language on similarity: The use of relational symbols improves young children’s performance on a mapping task. In K. Holyoak, D. Gentner, & B. Kokinov (Eds.), Advances in analogy research: Integration of theory and data from the cognitive, computational and neural sciences (pp. 274–281). Sophia: New Bulgarian University. Roberson, D., Davidoff, J., & Braisby, N. (1999). Similarity and categorisation:

13. Perceptual categorization

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Neuropsychological evidence for a dissociation in explicit categorisation tasks. Cognition, 71, 1–42. Semenza, C. (1999). Lexical-semantic disorders in aphasia. In G. Denes & L. Pizzamiglio (Eds.), Handbook of clinical and experimental neuropsychology (pp. 215–244). Hove: Psychology Press. Semenza, C., Denes, G., Lucchese, D., & Bisiacchi, P. (1980). Selective deficit of conceptual structures in aphasia: Class versus thematic relations. Brain and Language, 10, 243–248. Shallice, T. (1988). From neuropsychology to mental structure. Cambridge: Cambridge University Press. Sirigu, A., Duhamel, J.-R., & Poncet, M. (1991). The role of sensorimotor experience in object recognition. Brain, 114, 2555–2573. Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119, 3–22. Sloman, S. A., Malt, B. C., & Fridman, A. (2001). Categorization versus similarity: The case of container names. In U. Hahn & M. Ramscar (Eds.), Similarity and categorization (pp. 73–86). Oxford: Oxford University Press. Snowden, J., Goulding, P. J., & Neary, D. (1989). Semantic dementia: Autobiographical contribution to preservation of meaning. Cognitive Neuropsychology, 11, 265–288. Teuber, H. L., & Weinstein, S. (1956). Ability to discover hidden figures after cerebral lesions. Archives of Neurology and Psychiatry, 76, 369–379. Varley, R., Siegel, M., & Want, S. C. (2001). Severe impairments in grammar do not preclude theory of mind. Neurocase, 7, 489–493. Vignolo, L. A. (1999). Disorders of conceptual thinking in aphasia. In G. Denes & L. Pizzamiglio (Eds.), Handbook of clinical and experimental neuropsychology (pp. 273–288). Hove: Psychology Press. von Stockert, T., & Bader, L. (1976). Some relations of grammar and lexicon in aphasia. Cortex, 12, 49–60. Warrington, E. K. (1975). The selective impairment of semantic memory. Quarterly Journal of Experimental Psychology, 27, 635–657. Warrington, E. K., & Shallice, T. (1984). Category specific semantic impairments. Brain, 107, 829–854. Wernicke, K. (1874). Der Aphasische Symptomenkomplex. Breslau: Cohn & Weigert. Whitehouse, P., Caramazza, A., & Zurif, E. (1978). Naming in aphasia: Interacting effects of form and function. Brain and Language, 6, 63–74. Wyszecki, G., & Stiles, W. S. (1982). Color science. New York: Wiley. Zangwill, O. L. (1964). Intelligence in aphasia. In A. V. S. de Rueck & M. O’Connor (Eds), Disorders of language, pp. 261–274. London: J. & A. Churchill. Zurif, E., Caramazza, A., Meyerson, R., & Galvin, J. (1974). Semantic feature representation for normal and aphasic language. Brain and Language, 1, 167–187.

14 Visual agnosia H. Branch Coslett

Picture a table set for a holiday banquet with multiple place settings—each with knives, forks, spoons, plates, and glasses—as well as candelabras, serving bowls, condiments, chairs, and the table itself. The visual information that will ultimately yield an internal representation in which object identities are registered and their locations computed in a fashion that affords action, is registered by retinal cells that contain a variety of light-sensitive molecules that influence the firing rates of the cells. From this seemingly impoverished input that yields only a representation of light and, in a restricted spatial domain, color, the rich depiction of the visual world is generated by means of a series of transformations and elaborations. Although under normal circumstances visual processing is effortless and remarkably efficient, the construction of an internal representation of the visually perceived world around us is, in fact, complex, as witnessed by the fact that it may be disrupted in strikingly different manners by brain dysfunction. This chapter focuses on one aspect of visual processing—the manner in which visually presented objects are identified and how this process breaks down, culminating in the disorder of visual object agnosia. We start with a brief historical overview of the disorder. In an effort to frame the subsequent discussion, a brief description of the processes underlying visual processing will be presented. Classical disorders of visual object recognition as well as several recently described disorders will be discussed with reference to this theoretical framework.

Historical overview Interest in the neural basis of object recognition can be traced to the latter portion of the nineteenth century. In 1876, Hughlings Jackson reported a patient with a large tumor of the posterior portion of the right hemisphere who was unable to navigate in familiar places and failed to recognize people and places. Jackson concluded that the posterior region of the right hemisphere was crucial for visual memory and recognition. Perhaps the first experimental exploration of this issue was reported by Munk (1878), who reported that bilateral ablation of the upper convex

250 Coslett surface of the occipital lobes produced a phenomenon termed “Seelenblindheit” (or mindblindness) and characterized by a relatively preserved ability to negotiate complex environments but an inability to recognize objects. Thus, Munk’s dogs did not bump into furniture, walls, or people but were unable to recognize their masters or distinguish food from other items by vision alone. The most influential early account of object recognition deficits was provided by Lissauer (1888, 1890). Presaging later reports, Lissauer suggested that brain lesions could selectively disrupt the processing of color, form, and motion. He also introduced the first and still most commonly employed nosology for visual agnosia by distinguishing between “apperceptive” and “associative” agnosia. In his terminology, apperception referred to the “stage of conscious awareness of a sensory impression”. Thus, apperceptive agnosia was regarded as an impairment in the early visual processes by which an adequate internal representation of the object was achieved. Like other investigators, Lissauer distinguished between apperceptive agnosia and object recognition deficits attributable to primary visual loss; it is clear that apperceptive visual agnosia would not be diagnosed in the context of severe loss of visual acuity or profound visual field restriction. For Lissauer—and contemporary investigators as well—the boundary between low-level visual deficits and apperceptive agnosia is not always clear. Associative agnosia is characterized by preserved ability to compute a representation of the object but failure to “recognize” the object, as evidenced by inability to name or provide specific information that would unambiguously identify the object. In Lissauer’s view, recognition results from the simultaneous activation of the many attributes (sound, touch, smell, etc.) of an object that are linked to the visual form. Visual agnosia is differentiated from a loss of semantic knowledge by the fact that the deficit is modality specific; visual agnosics are able to identify objects on the basis of sound, description, or touch. Lissauer suggested that apperceptive and associative visual agnosia may be distinguished by assessing the ability to copy the object; apperceptive agnosics may be unable to copy even a simple figure whereas associative agnosics are able to copy a figure—sometimes with remarkable precision (Rubens & Benson, 1971)—but are unable to recognize the object. It should be noted that the very existence of visual object agnosia has been questioned by some investigators. Whereas Munk (1890) described the behavior of his dogs with the phrase “the dog sees but does not understand”, Pavlov (1927) argued that “the dog understands but does not see well enough.” Later, Bay (1953) argued that visual agnosia is attributable to primary visual disturbances, perhaps in conjunction with higher cognitive functions. Bender and Feldman (1972) also argued that visual recognition deficits reflect a combination of elementary visual processing problems in conjunction with deficits in memory, attention, and general intelligence.

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An information-processing account of visual recognition Although Lissauer’s (1890) distinction between apperceptive and associative visual agnosia remains a useful starting point in the discussion of these disorders, subsequent descriptions of clinical phenomena as well as recent developments in the understanding of visual object processing have demonstrated the model to be insufficient. In this section, we offer a brief account of the processes involved in visual object recognition that is based on recent advances in visual neuroscience. We will attempt to demonstrate that this model can account for many (but not all) of the reported disorders of visual object-processing disorders. Perhaps the most important insight into visual processing during the last century has been the recognition that different types of visual information are segregated, starting at the level of the retina; furthermore, although there are substantial interactions at many levels, this segregation persists in early visual processing and is evident in higher-level vision with respect to the distinction between the ventral “what” stream and the dorsal “where” (Ungerleider & Mishkin, 1982) or “how to” (Milner & Goodale, 1995) stream. This basic architecture is illustrated in Figure 14.1 depicting the types of representations computed by the nervous system and the processes that modulate these representations. Detailed physiologic and anatomic investigations in animals and more studies in human subjects involving functional imaging have confirmed Lissauer’s century-old contention that distinct cortical regions operating (at least in part) in parallel, subserve different functions. Attributes that appear to be processed in parallel include motion, color, depth, and multiple attributes regarding edges such as orientation, length, and angle. Influenced by relatively low-level visual routines such as “boundary marking” (e.g. Ullman, 1984), the latter attributes are grouped together to generate visual forms. Although the nature of the procedures by which low-level visual information is grouped was intensively investigated by the Gestalt psychologists among others (e.g. Kanizsa, 1976), these procedures remain poorly understood. Grouping of visual feature information occurs early in visual processing and is a prerequisite for all types of higher-level vision except perhaps motion perception. Despite the fact that a substantial body of evidence supports the view that visual processing proceeds in parallel fashion, healthy individuals do not “see” the world in a piecemeal fashion; thus, the information that is partially segregated in the course of early and intermediate visual processing must be linked together. This “binding problem” is not restricted to vision, of course, but represents a major challenge for accounts of virtually all sensory-motor and cognitive operations. Substantial experimental evidence suggests that the binding of visual information together to generate an integrated representation is mediated by a limited capacity operation typically referred to as “visual attention”. As suggested by the commonly used “spotlight” (Eriksen

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& Hoffmann, 1973; Posner, 1980), visual attention appears to be spatially based under most circumstances. Experimental evidence suggests that attention can also be allocated to other visual attributes, including color (Cave, 1999), motion, and even objects (Duncan, 1984; Vecera & Farah, 1994). The “binding” function of visual attention is illustrated by the phenomenon of “illusory conjunctions” reported by Treisman and Gelade (1980), Treisman (1985) and others (Cave, 1999; Prinzmetal et al., 2002). These investigators have demonstrated that when visual attention is “overloaded” in normal subjects, visual attributes can miscombine. For example, when presented with an array containing red “X ”s and green “T ”s for 200 ms, subjects may report seeing a red T even though no such stimulus was present in the array. These and similar findings have been taken as evidence that visual attention is the “glue” that links visual feature information computed in different brain regions. Note that for the sake of simplicity visual attention is indicated at only one level of processing in Figure 14.1; in fact, the effects of visual attention are apparent at multiple levels of processing (e.g. Moran & Desimone, 1985); indeed, in some investigations, the effects of visual attention have been demonstrated in the primary visual cortex (Vidyasagar, 1998). We will argue below that impairments in visual attention at different levels of processing may give rise to distinctly different syndromes. Functional imaging data (e.g. Corbetta, 1998), as well as data from brain lesion subjects, argue for a central role of the posterior parietal cortex in visual attention. Under normal circumstances, visual feature information is correctly spatially coregistered, generating a viewer-centered representation of the orientations and depths of the surfaces of an object as well as the discontinuities between the surfaces. This representation is similar in most important respects to the “2½D model” described by Marr (1982). The process of object processing culminates in a representation that makes explicit the form, shape, and volume of the object as well as the hierarchical relationships between the parts. This type of representation has been termed a “structural description” (Pinker, 1985; Riddoch & Humphreys, 1987) and is similar to the 3-D representation of Marr (1982) in that it is assumed to be perspectiveindependent; that is, it is a representation that is abstracted from the color, form, and surface information that is perspective invariant. Various lines of evidence suggest that the fusiform gyri and lateral occipital region are crucial anatomic substrates for the integrated feature representation and structural description systems (Grill-Spector, Knouf, & Kanwisher, 2004; Haxby et al., 2000 for reviews). Under normal circumstances, familiar objects are quickly and effortlessly recognized when viewed across a wide range of angles and perspectives. A bowl, for example, may be viewed from the side when sitting in a dishwasher, from below when stacked on a high shelf, or from above when clearing a table. Although the low-level visual information regarding surfaces, color, form, etc., is remarkably different in these circumstances, the visual feature and

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surfaces provided being markedly different, these forms are immediately recognized to be the same. In the context of Figure 14.1, the mechanism that supports object constancy is termed the view normalization system. The nature of the processes that mediate between the viewer-dependent, integrated feature representation and the perspective-independent or objectcentered structural description remain unknown. As reviewed briefly by Farah (2000), a variety of accounts have been proposed, from connectionist architectures to template matching procedures. Details of these proposals are beyond the scope of this chapter. The visual processing discussed to this point is in the service of object recognition—that is, knowledge of the form, function, name, and other attributes of entities in the environment. Following Lissauer (1888, 1890) and Wernicke (cited in 1977) as well as recent accounts of semantic representations (Allport, 1985; Rogers et al., 2004; Saffran & Schwartz, 1994; Warrington & Shallice, 1984), we suggest that recognition entails the simultaneous activation of the many aspects of object-specific knowledge; thus, as argued by Lissauer (1888), for example, recognition of a violin consists of the activation of stored knowledge regarding the sound, heft, feel, and manner of manipulation of the instrument.

Disorders of object processing Achromatopsia Achromatopsia is an acquired disorder of color perception characterized by a loss of the ability to distinguish color. The disorder varies in severity, from color desaturation to a complete loss of the sense of color. Some patients with the disorder state that they see the world in “black and white” or shades of gray. The defect often occurs in one visual field (or a portion thereof) but can involve the entire visual field. Depending on the location and extent of the underlying lesion, achromatopsia may be observed in isolation or in conjunction with other deficits in visual processing such as prosopagnosia, alexia, or superior visual field deficits (e.g. Pearlman, Birch, & Meadows, 1979). Presumably reflecting the fact that color is not a defining feature of most objects, achromatopsia is typically not associated with a profound object agnosia. Since Verrey’s initial report of the disorder in 1888, achromatopsia has been associated with lesions involving the lingual or fusiform gyri. Subsequent studies with static brain imaging (Damasio et al., 1980) and functional brain imaging have yielded generally similar results. Impaired motion perception Motion is a crucial element of visual perception; the importance of motion is illustrated by the fact that cells that appear to be optimized for motion perception may be identified at the retina, lateral geniculate, primary visual

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cortex, and a number of higher-level visual cortices, including MT (see below). Patients with relatively selective deficits in motion were reported almost a century ago but are relatively rare (Goldstein & Gelb, 1918; Potzl & Redlich, 1911). The most extensively investigated such patient, LM (Zihl, Von Cramon, & Mai, 1983), developed a profound impairment in the ability to detect motion after bilateral infarcts involving the posterior portions of the middle temporal gyri extending into the occipital lobe as well as adjacent subcortical white matter. LM was severely affected by her deficit. She did not perceive movement as a continuous process but stated that objects seemed to jump from one position to the next. When she poured water into a cup, the liquid appeared to be static, like a piece of ice. Although profoundly impaired in motion perception, LM performed well on other measures of visual processing. Her visual fields were full and she performed normally on tests of stereopsis, visual acuity, color perception, and critical flicker fusion. At least under most circumstances, LM exhibited no impairment in object recognition. Several patients have been reported whose object recognition is influenced by motion. Botez et al. (1965) reported two patients whose recognition of letters and objects was greatly facilitated by motion. A similar but perhaps less striking facilitation of recognition with movement was exhibited by the “visual form agnosic” reported by Benson and Greenberg (1971) as well as a patient reported by Horner and Massey (1986). We have observed this phenomenon in a number of patients with degenerative diseases preferentially involving the posterior portions of the hemispheres (that is, “posterior cortical atrophy”). Several lines of evidence point to the posterior portion of the middle temporal gyri as a critical structure for motion perception. As previously noted, LM’s lesions involved this region. Newsome and Pare (1988) reported that experimentally induced lesions in the posterior portion of the middle temporal gyri of monkeys caused a substantial deficit in motion perception without a concomitant impairment of spatial contrast sensitivity. Finally, a number of functional imaging studies showed that moving stimuli, such as an array of moving dots or shrinking/enlarging concentric rings of circles, reliably generate robust activation in the lateral occipito-temporal cortex bilaterally (Kable, Lease-Spellmeyer, & Chatterjee, 2002; Zeki, 1993). Visual form agnosia As noted above, information concerning visual features such as angle, orientation, and line length appears to be computed in parallel; we are unaware of patients with selective deficits involving individual features such as angle or orientation, perhaps because such an impairment would be expected to produce such a pervasive and severe “low-level” visual impairment that the patient would be considered too visually impaired to be agnosic. Several patients exhibiting substantial problems in the segregation of coherent

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regions of visual input have been reported under the term “visual form agnosia”. One such subject, Mr S., was reported by Benson and Greenberg (1971) and investigated in detail by Efron (1968). This 24-year-old man suffered carbon monoxide poisoning. Although intellectually preserved, he performed poorly when asked to name objects, drawings, letters, or faces. Testing of his visual processing revealed normal performance on tasks requiring the detection of differences in luminance, wavelength, area, and motion. He was substantially impaired, however, when asked to discriminate between visual objects that differed only in shape. Thus, for example, Mr S. could not reliably distinguish between a square and a tall thin rectangle (e.g. a height:width ratio of 4:1). DF, a woman who suffered carbon monoxide poisoning at the age of 34, also exhibited visual form agnosia (Milner & Heywood, 1989). Structural MRI demonstrated bilateral lesions involving the lateral occipital area. Like Mr S., this patient exhibited profound visual recognition problems and performed poorly on tasks requiring that she discriminate between different shapes. DF is of particular interest, however, because of her preserved ability to act on visual stimuli that she was unable to recognize. Although unable to discriminate between a square and tall rectangle, she performed normally with respect to hand posture and shape when asked to pick up the objects; for example, the distance between her thumb and index finger and timing of the movements of the fingers in the reach trajectory were normal. Thus, information regarding visual form that was not available for the purposes of object analysis was available to the motor system. Disorders of visual attention As noted briefly above, visual attention is a limited-capacity resource that serves to bind together information that is distributed across multiple brain regions to generate a representation in which information regarding shape, color, and movement are integrated (Figure 14.1). Impaired visual attention appears to play the major role in a number of disorders of visual object recognition. Perhaps the prototypical syndrome of this type is “simultanagnosia”, an inability to “see” more than one object in an array (Wolpert, 1924). The first detailed description of this syndrome was by Balint (1909), who described a patient with bilateral posterior parietal infarcts. Although able to identify visually presented familiar objects when presented in isolation, he exhibited a striking difficulty in the processing of visual arrays. For example, when shown a letter and a triangle, he reported seeing only the letter; when told that a second object was present, he reported the triangle but no longer saw the letter. As Balint’s patient had normal visual fields and visual acuity, the disorder could not be attributed to low-level visual processing deficits. Similar patients have been reported by a number of investigators (Coslett & Saffran, 1991; Holmes, 1918; Luria, 1959). Several different types of simultanagnosia may be identified. In one variant,

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Figure 14.1 An information-processing model of the processes involved in object processing.

termed “ventral simultanagnosia” by Farah (2004), patients are impaired in the processing of arrays but also in the recognition of single objects. For example, when confronted with a complex object such as a car, subjects with this disorder may report only a tire; similarly, when shown the word “table”, subjects may not see the entire word but report constituent letters, often identifying the word in a letter-by-letter fashion. Performance of patients with this disorder is strongly influenced by object familiarity; for example, they may read the word “table” correctly but misread the less common word “sable”; nonword letter strings (e.g. “tarle”) present the greatest difficulty. Unlike patients with visual form agnosia, dorsal simultanagnosia (see below), or other types of “apperceptive” agnosia, ventral simultanagnosics do not behave as if they are profoundly visually impaired; that is, they do not walk into objects, stumble over chairs, etc., as noted by Farah (2004). Although these patients appear to be able to recognize only one object at a time, they appear to “see” more than that. Patients with “dorsal” simultanagnosia exhibit a somewhat different and, often, far more dramatic deficit than that observed in ventral simultanagnosia. Patients with this disorder will often behave as if they are blind; for example, we have reported a patient who fell over a dining room table while walking across a room to reach a light switch. In contrast to patients with

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ventral simultanagnosia, patients with this disorder often report the largest meaningful “object” in an array. Thus, when confronted with a familiar word such as “rock”, the patient is likely to respond correctly, whereas when confronted with a nonword letter string, the patient may name only a single letter (subject HM; Coslett & Saffran, 1991). Object size does not appreciably influence performance. We have recently suggested that dorsal simultanagnosia may be further subdivided. On our analysis, one form of dorsal simultanagnosia may be attributable to an impairment in the process by which visual attention is allocated or serves to integrate visual feature information. We have recently reported a simultanagnosic patient, for example, who exhibited a striking deficit in “disengaging” visual attention (Pavese, Coslett, Saffran, & Buxbaum, 2002). The critical data in support of this claim come from a series of investigations in which the patient, IC, was asked to report two vertically arrayed stimuli presented with a computer. IC reported both items correctly on only 6% of trials with stimulus duration of up to 30 s. In a second condition, one of the stimuli was extinguished after a short time, thereby “releasing” attention; IC reported both items on 55% of trials in this condition, suggesting that his deficit was, at least in part, attributable to a disturbance of disengaging attention. As described above, in some accounts of visual processing, attention is assumed to be crucial for the integration of visual feature information computed in parallel into an integrated representation. These accounts predict that patients with impaired visual attention would produce “illusory conjunctions” characterized by the incorrect combination of visual features. Several such patients have been reported (Pavese et al., 2002; Robertson, Treisman, Freidman-Hill, & Grabowecky, 1997). We have investigated a patient, for example, whose report of letters in an array appeared to reflect the miscombination of structural elements of the letters; for example, when presented with P Q the patient reported “R O”. These errors were not encountered when the letters were presented in different color inks (e.g. red P and blue Q). This finding is similar to Luria’s report that a simultanagnosic patient reported a Star of David when shown overlapping triangles of the same color; when one triangle was blue and the other red, however, the patient reported seeing only one triangle (Luria, 1959). Finally, we have suggested that simultanagnosia may also reflect not only a disturbance of “binding” visual feature information but, in some instances, an impairment in linking object location and identity (Coslett & Chatterjee, 2003). Consistent with this perspective, one subject with simultanagnosia was impaired in reporting not only more than one object in an array, but also more than one attribute of a single object. Disorders of visual attention are a prominent feature of the “simultanagnosia-like” disturbance encountered in other conditions such as the syndrome of “posterior cortical atrophy” (Benson et al., 1988). The most common cause of this syndrome is Alzheimer’s disease. Like patients with simultanagnosia from focal parieto-occipital lesions, these patients often

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identify single objects relatively well but are substantially impaired in the processing of arrays. These patients are often severely impaired in everyday activities such as finding an item in the refrigerator or the butter dish on the table. They may be unable to find their way in their own home; we have encountered a number of patients whose visual world is so “confusing” that they close their eyes when walking or searching a complex array. The visual processing deficit in these patients differs in one telling way from that of simultanagnosic patients with focal parieto-occipital lesions: they exhibit a striking effect of object size. We (Coslett & Saffran, 1996; Saffran, Fitzpatrick-DeSalme, & Coslett, 1990) and others have reported patients who can name a small picture or word yet are unable to name the same stimulus. We reported one patient, for example, who was able to read the word CAT when printed in medium-size type (e.g. 2 cm in height), yet, when shown the same stimulus in large type, she reported seeing only an “A”. One year later, she reported seeing the word CAT written in small type but saw only a “T” when shown the word in medium-size type. We have suggested that these and other findings exhibited by these patients are consistent with the hypothesis that the patients suffer from a pathologic restriction in their capacity to integrate visual feature information. Additional findings relevant to the role of visual attention in visual processing comes from subjects with “attentional dyslexia”. First described by Shallice and Warrington (1977), this disorder has been reported in patients with bilateral posterior lesions as well as with degenerative diseases affecting the parieto-occipital region (such as posterior cortical atrophy). Although there is variability with respect to the performance of these patients, the cardinal feature is an inability to identify words flanked by additional letters or numbers (Shallice & Warrington, 1977); these patients may, for example, be unable to identity any word in the following letter string “mtableq”. Additionally, we have reported a patient with this disorder in the context of Alzheimer’s disease who reported seeing words generated by “blending” letters from nearby words; thus, shown the word pair bike lake, the patient responded “like bake”. Impairments in the view normalization system Warrington and Taylor (1973) provided the first systematic exploration of the mechanism by which object constancy is achieved. They asked patients to name two sets of 20 objects, one depicting the object in a canonical or standard view and the other in an unusual view (Figure 14.2). Subsequently, Warrington and Taylor (1978) asked subjects to indicate whether two objects viewed from different perspectives were the same or different objects. They found that subjects with lesions involving the posterior portion of the right (nondominant) hemisphere were selectively impaired in the recognition of the unusual views of these objects. The mechanism(s) by which object constancy is achieved remain unclear.

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Figure 14.2 An example of a stimulus presented from unusual (above) and canonical (below) views.

Humphreys and Riddoch (1984; see also Riddoch & Humphreys, 1986) have suggested that the deficit may be observed for different reasons. Thus, they reported one patient who appeared to rely on distinctive feature information; other patients, in contrast, have been found to be particularly sensitive to foreshortening (see also Warrington & James, 1986), suggesting that these patients are unable to generate a representation of the object relative to its principal axis. Although the phenomenon of object constancy has received substantial attention over the years, the relevance of performance on the “unusual views” and related tasks to normal vision is uncertain. Thus, as noted by Farah (2000), although patients with lesions involving the posterior portion of the right hemisphere typically exhibit impairment in these tasks (e.g. Warrington & Taylor, 1973; Riddoch & Humphreys, 1986), these patients do not typically exhibit impairments in object recognition in naturalistic settings, making the relevance of their performance on this task unclear with respect to object processing.

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Impairment-integrated visual features and the structural description system: associative agnosia A number of well-studied patients whose deficits suggest impairment of the integrated visual feature representation or the structural description system have been reported (Davidoff & Wilson, 1985; Levine, 1978; Levine & Calvanio, 1989; see Farah, 2004, for a comprehensive review). Rubens and Benson (1971) reported a patient who exhibited a striking form of associative agnosia after a hypotensive episode. Elementary visual function was normal except for right hemianopia; language and general intellectual functions were preserved. Although unable to name most visually presented objects, he drew accurate representations of objects and copied line drawings accurately, suggesting that his deficit affected a level of visual processing after which visual form had been computed and visual features integrated. How can this patient be accommodated in the context of Figure 14.1? From Lissauer’s initial account to the present, disruption of integrated feature information or the structural description system has been assumed to cause the pattern of deficits displayed by the patient reported by Rubens and Benson (1971). Associative visual agnosia is differentiated from loss of semantics by the fact that, when queried verbally or by means of auditory or tactile input, the patients are able to provide appropriate information about objects that they are unable to recognize visually; thus, when asked to provide a verbal description of a hammer, for example, an associative agnosic would be expected to describe its function, heft, and sound as well as demonstrate its manner of manipulation. Similarly, the patient would be expected to be able to name the hammer after handling it. Associative agnosia is typically differentiated from lower-level visual deficits in several ways. First, patients with associative agnosia often see well enough to describe or copy stimuli; as noted, a number of investigators (Humphreys & Riddoch, 1987; Rubens & Benson, 1971; see Farah, 2004) have reported patients able to produce precise drawings of objects that they were unable to recognize. This phenomenon is illustrated in Figure 14.3; the patient was asked to copy a drawing of a carrot; after having generated the copy depicted in Figure 14.3, the patient identified the object as “something you can eat, maybe a strawberry”. The ability to produce relatively precise copies of visual stimuli has led some investigators to suggest that structural descriptions may be intact in associative agnosia. As discussed by Farah (2000), this seems unlikely for several reasons. First, although in some instances quite precise, the copies of visual agnosics are typically produced in a “slavish” and painstaking fashion, presumably reflecting a reliance on the exact physical attributes of the stimulus with little or no “top-down” input from stored knowledge of object appearance. This point is illustrated by the copy depicted in Figure 14.3 in which an extraneous sinusoidal line was accurately reproduced by the patient. The patient included the line in his rendering without exhibiting any evidence that he thought it to be out of place.

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Figure 14.3 A visual agnosic’s copy of a line drawing of a carrot on which an extraneous sinusoidal line had been traced.

Additional evidence supporting the claim that intact stored information regarding object form is not available to associative agnosics comes from the observation that the quality of the copies typically is strongly influenced by the richness of the visual image; thus, they typically perform best with real objects, less well with pictures, and worst with line drawings. This hierarchy would not be expected if all three types of stimuli contacted the same structural description. Finally, it should be noted that when asked to match or sort complex nonobject figures, all associative agnosics of which we are aware exhibit impairments (Humphreys & Riddoch, 1987; Ratcliff & Newcombe, 1982; see Farah, 2004, for discussion). Although this does not prove that these patients do not have access to intact structural descriptions, it strongly suggests that they have some degree of impairment in the processes by which structural descriptions are accessed. Finally, it should be emphasized that although the model depicted in Figure 14.1 provides a useful framework for considering the general principles involved in visual processing and their breakdown, it does not readily accommodate the full range of agnosic performance. One well-studied patient, HJA (Riddoch & Humphreys, 1987) illustrates this fact. HJA exhibited normal or near normal performance on a variety of tasks. He performed well on size and orientation judgment tasks. His detection of a visual stimulus that differed from the array by one feature was not influenced by array size; for example, his good performance in detecting a red T in an array of green Ts was not influenced by the number of green Ts, suggesting that he could process visual information in a spatially parallel fashion. He performed normally at identifying silhouettes but was impaired in identifying line drawings. He was particularly impaired on tasks requiring that local visual feature information be integrated into a perceptual whole; thus, HJA was at chance level on an object decision task, in which the stimuli were composed of

262 Coslett parts of real objects, and performed poorly with Navon stimuli. Despite these difficulties, however, HJA produced well-formed and, in some instances, elaborate copies of complex visual stimuli. Thus, in some respects, HJA, designated an “integrative” agnosic by Riddoch and Humphreys (1987), appears to be an associative agnosic (Farah, 2004), whereas in other regards his performance is more typical of apperceptive agnosia (Riddoch & Humphreys, 2003). A final point of interest in this context concerns the sometimes robust differences in performance as a function of stimulus category. Three broadly defined classes of visual stimulus may be identified: words, objects, and faces. As discussed in some detail by Farah (2004), patients with recognition deficits specific to words, as well as patients with recognition deficits specific to faces, have been repeatedly described. Patients exhibiting impaired recognition of objects as compared to faces and words are rare (Buxbaum et al., 1996); furthermore, patients with impaired recognition of objects but normal word and face processing have not, to our knowledge, been reported. There are several possible explanations for this pattern; first, one might suggest that the recognition of faces, words, and objects is dependent on different neural processes and substrates. Support for such an account comes from multiple functional imaging studies demonstrating activation for faces (fusiform face area; see Haxby et al., 2000), scenes and places (parahippocampal place area; see Epstein & Kanwisher, 1998), and objects (lateral occipital complex, see Grill-Spector, 2003). Alternatively, these findings led Farah (2004) to propose that two distinct but interactive modes of object processing subserve stimulus recognition; by her account, one mechanism is specialized for objects that are processed as a unit, that is, with relatively little decomposition into simpler parts; various lines of evidence support the view that faces are processed in this manner. A second mechanism is specialized for stimuli that undergo substantial decomposition; for these items, the parts into which they are segregated may be discrete objects themselves. As they are composed of a finite number of discrete objects and their identity is entirely determined by the constituent units, words may represent the prototypical stimulus for the decomposition procedure.

Conclusion Patients with lesions involving posterior brain regions may present with a bewildering array of deficits, ranging from impairment in registering visual information to relatively preserved vision but a failure to recognize objects. We have suggested that the understanding of these complex disorders of object recognition may be facilitated by a consideration of the basic processes underlying vision. To this end, we have briefly described a model of the processes involved in object recognition and attempted to link well-described clinical syndromes to disruption of these processes. Although much remains to be learned, the continued application of the approach employed so successfully by Professor Vignolo—that is, theoretically motivated investigation

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of patients with brain dysfunction—is likely to provide important insights into visual agnosia and object processing more generally.

References Allport, D. A. (1985). Distributed memory, modular subsystems and dysphasia. In S. K. Newman & R. Epstein (Eds.), Current perspectives in dysphasia (pp. 32–60). Edinburgh: Churchill Livingstone. Balint, R. (1909). Seelenlahmung des “Schauens”, optische Ataxie, raumliche Störung der Aufmerksamkeit. Monatsschrift für Psychiatrie und Neurologie, 25, 51–81. Bay, E. (1953). Disturbances of visual perception and their examination. Brain, 76, 515–550. Bender, M., & Feldman, M. (1972). The so-called “visual agnosias”. Brain, 95, 173–86. Benson, D. J., Davis R. J., & Snyder, B. D. (1988). Posterior cortical atrophy. Archives of Neurology, 45, 789–793. Benson, D. F., & Greenberg, J. P. (1971). Visual form agnosia. Archives of Neurology, 20, 82–89. Botez, M. I., Serbanescu, T., & Vernea, I. (1965). Visual static agnosia with special reference to liteal agnosic alexia. Neurology, 5, 1101–1111. Buxbaum, L. J., Glosser, G., & Coslett, H. B. (1996). Relative sparing of object recognition in alexia-prosopagnosia. Brain and Cognition, 32, 202–205. Cave, K. R. (1999). The FeatureGate model of visual selection. Psychological Research, 62, 182–194. Corbetta, M. (1998). Frontoparietal cortical networks for directing attention and the eye to visual locations: Identical, independent, or overlapping neural systems? Proceedings of the National Academy of Science of the USA, 95, 831–838. Corbetta, M., & Shulman, G. L. (1998). Human cortical mechanisms of visual attention during orienting and search. Philosophical Transactions of the Royal Society of London. Series B, 353, 1353–1362. Coslett, H. B., & Chatterjee, A. (2003). Balint’s syndrome. In T. Feinberg & M. Farah Eds.), Behavioral neurology and neuropsychology. (pp. 325–336). New

York: McGraw-Hill. Coslett, H. B., & Saffran, E. (1991). Simultanagnosia. To see but not two see. Brain, 114, 1523–1545. Coslett, H. B., & Saffran, E. (1996). Visuospatial functioning. In R. Morris (Ed.), The cognitive neuropsychology of Alzheimer-type dementia (pp. 193–205). New York, Oxford University Press. Damasio, A. R., Damasio, H., & Chui, H. C. (1980). Neglect following damage to frontal lobe or basal ganglia. Neuropsychologia, 18, 123–132. Davidoff, J., & Wilson, B. (1985). A case of visual agnosia showing a disorder of presemantic visual classification. Cortex, 21, 121–134. Duncan, J. (1984). Selective attention and the organization of visual information. Journal of Experimental Psychology. General, 113, 501–517. Efron, R. (1968). What is perception? Boston Studies in Philosophy of Science, 4, 137–173. Epstein, R., & Kanwisher, N. (1998). A cortical representation of the local visual environment. Nature, 392, 598–601. Eriksen, C. W., & Hoffmann, J. E. (1973). The extent of processing of noise elements

264

Coslett

during selecting encoding from visual displays. Perception and Psychophysics, 12, 201–204. Farah, M. J. (2000). The cognitive neuroscience of vision. Malden: Blackwell. Farah, M. J. (2004). Visual agnosia (2nd ed.). Cambridge, MA: MIT Press. Goldstein, K. M., & Gelb, A. (1918). Psychologische Analysen hirnpathologischer Falle auf Grund von Untersuchungen Hirnverletzter. Zeitschrift für die Neurologie and Psychiatrie, 41, 1–142. Grill-Spector, K. (2003). The neural basis of object perception. Current Opinion in Neurobiology, 13, 1–8. Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. et al. (2000). The distributed human neural system for face perception. Trends in Cognitive Sciences, 4, 223. Holmes, G. (1918). Disturbances of visual orientation. British Journal of Ophthalmology, 2, 449–468. Horner, J., and Massey, E. W. (1986). Dynamic spelling alexia. Journal of Neurology, Neurosurgery and Psychiatry, 49, 455–457. Humphreys, G. W., & Riddoch, M. J. (1984). Routes to object constancy: Implications from neurological impairments of object constancy. Quarterly Journal of Experimental Psychology, 36A, 385–415. Humphreys, G. W., & Riddoch, M. J. (1987). The fractionation of visual agnosia. In G. W. Humphreys & M. J. Riddoch (Eds.), Visual object processing: A cognitive neuropsychological approach. Hove: Lawrence Erlbaum Associates Ltd. Jackson, J. H. (1876). Case of large cerebral tumor without optic neuritis and with left hemiplegia and imperception. Royal London Ophthalmic Hospital Reports, 8, 434–444. Kable, J. W., Lease-Spellmeyer, J., & Chatterjee, A. (2002). Neural substrates of action event knowledge. Journal of Cognitive Neuroscience, 14, 795–805. Kanizsa, G. (1976). Subjective contours. Scientific American, 234, 48–52. Levine, D., & Calvanio, R. (1989). Prosopagnosia: A defect in visual configural processing. Brain and Cognition, 10, 149–170. Levine, D. N. (1978). Prosopagnosia and visual object agnosia: A behavioral study. Neuropsychologia, 5, 341–365. Lissauer, H. (1888). A case of visual agnosia with a contribution to theory. Cognitive Neuropsychology, 5, 157–192. Lissauer, H. (1890). Ein Fall von Seelenblindheit Nebst Einem Beitrage zur Theorie derselben. Archiv für Psychiatrie und Nervenkrankheiten, 21, 222–270. Luria, A. R. (1959). Disorders of “simultaneous perception” in a case of bilateral occipitoparietal brain injury. Brain, 83, 437–449. Marr, D. (1982). Vision. A computational investigation into the human representation and processing of visual information. New York: WH Freeman. Milner, A., & Goodale, M. (1995). The visual brain in action. New York: Oxford University Press. Milner, A. D., & Heywood, C. A. (1989). A disorder of lightness discrimination in a case of visual form agnosia. Cortex, 25, 489–494. Moran, J., & Desimone, R. (1985). Selective attention gates visual processing in extrastriate cortex. Science, 229, 782–784. Munk, H. (1878). Weitere Mittheilungen zur Physiologie der Grosshirnrinde. Archiv für die Anatomie und Physiologie, 2, 161–178. Munk, H. (1890). Über die Functionen der gross Hirnwinde, (2 Aufl). Berlin: Aug. Hirschwald.

14. Visual agnosia

265

Newsome, W., & Pare, E. (1988). A selective impairment of motion perception following lesions of the middle temporal visual area (MT). Journal of Neuroscience, 8, 2202–2211. Pavese, A., Coslett, H. B., Saffran, E., & Buxbaum, L. (2002). Limitations of attentional orienting. Effects of abrupt visual onsets and offsets on naming two objects in a patient with simultanagnosia. Neuropsychologia, 40, 1097–1103. Pavlov, I. P. (1927). Conditioned reflexes. London: Oxford. Pearlman, A. L., Birch, J., & Meadows, J. C. (1979). Cerebral color blindness: An acquired defect in hue discrimination. Annals of Neurology, 5, 253–261. Pinker, S. (1985). Visual cognition: An introduction. Cambridge, MA: MIT Press. Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3–25. Potzl, O., & Redlich, E. (1911). Demonstration eines Falles von bilateraler Affektion bei der Okzipitallappen. Weiner Klinsche Wochenschrift, 24, 517–518. Prinzmetal, W., Ivry, R. B., Beck, D., & Shimizu, N. (2002). A measurement theory of illusory conjunctions. Journal of Experimental Psychology and Human Perception and Performance, 28, 251–269. Ratcliff, G., & Newcombe, F. (1982). Object recognition: Some deductions from the clinical evidence. In A. W. Willis (Ed.), Normality and pathology in cognitive functions. New York: Academic Press. Riddoch, M. J., & Humphreys, G. W. (1986). Neurological impairments of object constancy: The effects of orientation and size disparities. Cognitive Neuropsychology, 3, 207–224. Riddoch, M. J., & Humphreys, G. W. (1987). A case of integrative visual agnosia. Brain, 110, 1431–1462. Robertson, L., Treisman, A., Freidman-Hill, S., & Grabowecky, M. (1997). The interaction of spatial and object pathways: Evidence from Balint’s syndrome. Journal of Cognitive Neuroscience, 9, 295–317. Rogers, T., Lambon Ralph, M., Garrard, P., Bozeat, S., McClelland, J., Hodges, J., et al. (2004). Structure and deterioration of semantic memory: A neuropsychological and computational investigation. Psychological Review, 111, 205–235. Rubens, A. B., & Benson, D. F. (1971). Associative visual agnosia. Archives of Neurology, 24, 305–316. Saffran, E., Fitzpatrick-DeSalme, E., & Coslett, H. (1990). Visual disturbances in dementia. In M. Schwartz (Ed.), Modular deficits in Alzheimer-type dementia (vol. 44, pp. 297–327). Cambridge, MA: MIT Press. Saffran, E. M., & Schwartz, M. F. (1994). Impairments of sentence comprehension. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 346, 47–53. Shallice, T., & Warrington, E. K. (1977). The possible role of selective attention in acquired dyslexia. Neuropsychologia, 15, 31–41. Treisman, A., & Gelade, G. (1980). A feature integration theory of attention. Cognitive Psychology, 12, 97–136. Treisman, A. S. J. (1985). Search asymmetry: A diagnostic for preattentive processing of separable features. Journal of Experimental Psychology: General, 114, 285–310. Ullman, S. (1984). Visual routines. Cognition, 18, 97–159. Ungerleider, L. G., & Mishkin, M. (1982). Two cortical visual systems. In D. J. Ingle, M. A. Goodale, & R. J. W. Mansfield (Eds.), Analysis of visual behavior (pp. 549–586). Cambridge, MA: MIT Press.

266

Coslett

Vecera, S. P., & Farah, M. J. (1994). Does visual attention select objects or locations? Journal of Experimental Psychology: General, 123, 146–160. Vidyasagar, T. R. (1998). Gating of neuronal responses in macaque primary visual cortex by an attentional spotlight. Neuroreport, 9, 1947–1952. Warrington, E. K., & James, M. (1986). Visual object recognition in patients with right hemisphere lesions: Axes or features? Perception, 15, 355–366. Warrington, E. K., & Shallice, T. (1984). Category specific semantic impairment. Brain, 107, 829–854. Warrington, E. K., & Taylor, A. M. (1973). The contribution of the right parietal lobe to object recognition. Cortex, 9, 152–164. Warrington, E. K., & Taylor, A. M. (1978). Two categorical stages in object recognition. Perception, 7, 695–705. Wolpert, I. (1924). Die Simultanagnosie: Störung der gesamtauffassung. Zeitschrift für die Gesamte Neurologie und Psychiatrie, 93, 397–413. Zeki, S. (1993). A vision of the brain. Oxford: Blackwell Scientific. Zihl, J., Von Cramon, D., & Mai, N. (1983). Selective disturbance of movement vision after bilateral brain damage. Brain, 106, 313–340.

15 Auditory agnosia Marie Di Pietro, Marina Laganaro, and Armin Schnider

Brain damage may lead to hearing acuity deficits or auditory recognition impairments with spared hearing. These latter syndromes will be the focus of this chapter. Regarding hearing acuity impairments after brain damage, Wernicke and Friedländer (1893) reported the case of a patient who was unable to hear any sound following bitemporal lesions. This rare disorder, called cortical deafness, refers to patients who behave like deaf people, and whose cortical auditory potentials are abolished by bilateral primary to auditory primary area destruction. Griffiths (2002) has recently proposed the term cerebral deafness instead of cortical deafness in reference to the causative lesion: reports following Wernicke and Friedländer (1893) confirmed that cortical deafness is always associated with bilateral lesions affecting the primary auditory area in Heschl’s gyrus in the superior temporal gyrus and subcortical extension (Graham, Greenwood, & Lecky, 1980; Mendez & Geehan, 1988; Tanaka, Kamo, Yoshida, & Yamadori, 1991). The term auditory agnosia was introduced by Freud (1891) in 1891 and refers to the inability to recognize auditory material, despite normal sound detection. Unlike cerebral deafness (Michel & Peronnet, 1980), auditory cortical potentials are typically present in auditory agnosia (Lambert, Eustache, Lechevalier, Rossa, & Viader, 1989; Lechevalier & Iglesias, 1997; Lechevalier et al., 1984; Tanaka, Yamadori, & Mori, 1987). Different forms of auditory agnosia have been described depending on the nature of the stimulus and the domain investigated. Agnosias for speech, environmental sounds, and music have been identified. When the impaired perception concerns verbal sounds, the disorder is called verbal auditory agnosia or word deafness; when it concerns nonverbal sounds and noises, the disorder is called nonverbal auditory agnosia or environmental sounds agnosia. When it concerns music, it is called amusia. In addition, a spatial auditory localization disorder has been demonstrated. Although cases of dissociated auditory agnosia, word deafness, or amusia have been reported, the disorder frequently affects all auditory domains and is then called global auditory agnosia. Initial cortical deafness may develop into general auditory agnosia with impaired recognition of environmental sounds, music, and voices. This overlap of impairments has led some authors

268 Di Pietro, Laganaro, Schnider to suggest that auditory agnosia constitutes a unitary disorder resulting from a single deficit of sound recognition (Albert & Bear, 1974; Auerbach, Allard, Naeser, Alexander, & Albert, 1982; Buchtel & Stewart, 1989; Mendez & Geehan, 1988; Tanaka et al., 1987). Indeed, several neuropsychological and psychophysical studies found a deficit in both auditory-temporal and spectral pattern processing in patients with auditory agnosia (Auerbach et al., 1982; Buchtel & Stewart, 1989; Coslett, Brashear, & Heilman, 1984; Griffiths et al., 1997b; Mendez & Geehan, 1988; Motomura, Yamadori, Mori, & Tamaru, 1986; Patel, Peretz, Tramo, & Labreque, 1998; Tanaka et al., 1987). These findings may suggest that speech, environmental, and musical sounds share spectrotemporal features whose impaired processing would lead to a deficit in each auditory domain. In this chapter, we will review the major forms of auditory processing disorders in adults and children. The different syndromes will be analyzed according to the following classification: • •

verbal auditory agnosia (word deafness) and associated syndromes (aprosodia, phonagnosia) nonverbal auditory agnosia (auditory agnosia) and associated syndromes (auditory spatial deficits, music perception deficits).

In addition, recent functional neuroimaging studies (positron emission tomography (PET) and functional magnetic resonance imaging (fMRI)) on auditory processing in controls and brain-damaged patients with different forms of auditory agnosia will be discussed.

Domain-specific auditory agnosia Reports of clinical cases allowed dissociating several auditory disorders in the verbal and nonverbal domain. Impaired verbal recognition with preserved nonverbal sound recognition is called verbal auditory agnosia, agnosia for verbal sounds, or word deafness. The opposite dissociation, agnosia for nonverbal sounds, sound agnosia, or auditory agnosia, was also described (Vignolo, 1982). In the nonverbal domain, a distinction is made between apperceptive and associative deficits. Additional circumscribed syndromes are amusia, phonagnosia, aprosodia, and spatial auditory deficits, which will be discussed below. Word deafness The inability to perceive spoken language despite intact perception of environmental sounds is called word deafness (Lichtheim, 1885). Patients with word deafness often complain of perceiving words as foreign words or meaningless sounds and that people talk too fast. In most cases, the syndrome is associated with aphasia, but cases of pure word deafness with intact language

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have been described (Auerbach et al., 1982; Spreen, Benton, & Fincham, 1965). A recent reanalysis of a patient (A.L.) (Pinard, Chertkow, Black, & Peretz, 2002), previously reported as having pure word deafness, suggested that his impairment indeed extended to environmental sounds, music, and voice. In reference to the three-step model of word comprehension proposed by Ellis and colleagues (Ellis, Franklin, & Crerar, 1994), several forms of word comprehension deficits can be distinguished depending on the level of impairment (auditory analysis; prelexical, lexical, or post-lexical access). A defect at the level of the auditory analysis system leads to word deafness (or word sound deafness) and corresponds to verbal auditory agnosia. Repetition and phoneme discrimination or identification are impaired. This form is distinct from word meaning deafness, which refers to difficulties in accessing semantics from speech. The existence of two types of word meaning deafness has been proposed, on the basis of the distinction between a pre- and a postlexical problem. A typical case of pre-access or word form deafness is illustrated by patient M.K. (Franklin, Turner, Lambon Ralph, Morris, & Bailey, 1996), who presented with impaired auditory lexical decision and intact phoneme discrimination. By contrast, a patient with post-access or word meaning deafness performs normally in auditory lexical tasks, but produces semantic errors in comprehension tasks (Franklin, Howard, & Patterson, 1994; Franklin et al., 1996). Word deafness was initially described in patients with deep left temporal lesions (Kussmaul, 1877; Lichtheim, 1885), but more recent reports indicate that lesions may include the primary auditory cortex (Heschl’s gyrus) and adjacent white matter bilaterally (Auerbach et al., 1982; Buchtel & Stewart, 1989; Coslett et al., 1984; Kazui, Naritomi, Sawada, Inoue, & Okuda, 1990; Tanaka et al., 1987). Some studies suggested that word deafness may result from a disconnection between Wernicke’s area and secondary cortical auditory areas (Coslett et al., 1984; Polster & Rose, 1998). Word deafness associated with epileptic seizures in children was for the first time described by Landau and Kleffner (1957). This syndrome, now called Landau–Kleffner syndrome (LKS) or acquired epileptiform aphasia, is an epileptic condition with severe deficits in auditory comprehension. The auditory comprehension deficits are associated with an EEG showing epileptic discharges in the temporal regions, mainly during sleep (Deonna & Roulet, 1995). Recovery of this receptive language disorder is variable and may be sudden or progressive (Deonna & Zesiger, 1997). Language production may also be impaired. In addition, a phonological short-term memory problem has been consistently found, even in patients presenting with good language recovery. The memory impairment has been related to residual language difficulties after recovery (Metz-Lutz, de Saint Martin, Hirsch, Maquet, & Maresceaux, 1999). In search of an underlying impairment in word deafness, neurophysiological and neurolinguistic studies demonstrated deficits in temporal resolution of

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acoustic signals (Albert & Bear, 1974; Auerbach et al., 1982) as well as in phonemic and pre-phonemic discrimination (Albert & Bear, 1974; Auerbach et al., 1982; Lambert et al., 1989; Motomura et al., 1986; Saffran et al., 1976; Tanaka et al., 1987; Wang, Peach, Xu, Schneck, & Manry, 2000). Auerbach et al. (1982) reported a right-handed patient who suffered from word deafness after bilateral lesions. The patient complained that speech sounded like “foreign language”, and that people were talking fast. Pure tone audiogram was normal. He had no aphasia and recognized people from their voices. No defect in environmental sound recognition or sound localization was found. The authors first evaluated the patient with two tasks of temporal acuity discrimination. In the “click fusion threshold” task, the patient heard two clicks with a varying interstimulus interval (ISI) and was asked to report whether one or two clicks had been presented. In the “click-counting” task, binaural clicks were presented in a 1–2-s interval, and the patient was asked to count the clicks. The patient had severe difficulty in both tasks. In the click fusion threshold task, the patient was unable to distinguish clicks below 30 ms ISI, while normal controls distinguished two clicks at 1–3 ms ISI. A similar deficit was found in the click-counting task, during which the patient accurately counted at rates inferior to 2 clicks per second, but performed below controls who accurately counted at rates up to 11 clicks per second. In a second part of the experiment, the authors tested the hypothesis of a phoneme discrimination defect that could account for their patient’s difficulty in word comprehension. Tasks of vowels and consonant–vowel (CV) discrimination were used. Vowels and consonants differ in the following way: while vowels are characterized by steady-state frequencies (durations of 100–400 ms), CV combinations such as /ba/ /pa/ contain consonants of rapid formant transitions within the first 40 ms of the onset of the stimulus. Results in vowels versus CV discrimination showed that while the patient had normal recognition of vowels, he was severely impaired in CV syllables identification, especially when the two initial consonants in CV syllables only differed by the place of articulation (/pa/ /ta/ /ka/). Thus, Auerbach and colleagues demonstrated that the phonemic discrimination deficit in their patient was due to a temporal acuity disorder. They characterized this pattern of impairment as “pre-phonemic”. According to their findings, and according to other cases reported in the literature (Chocholle, Chedru, Bolte, Chain, & Lhermitte, 1975; Denes & Semenza, 1975; Saffran, Marin, & Yeni-Komshan, 1976), Auerbach et al. (1982) suggested that two types of word deafness might exist. One type (apperceptive) is pre-phonemic in nature, explicable in terms of a defect in the temporal auditory acuity, which would impair verbal and nonverbal sounds. This pre-phonemic type would be associated with bitemporal lesions. The other type is characterized by a deficit in verbal sounds only. This defect would be associated with left unilateral lesions. Other studies confirmed the role of temporal processing in pure word deafness (Albert & Bear, 1974; Tanaka et al., 1987). Albert and Bear (1974) found that their patient’s comprehension significantly improved when the

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speaking rate was reduced to 1/3 of the normal rate (rate dependency). In a nonlinguistic task (click-fusion task), the patient differed significantly from normal controls, as he was unable to distinguish two clicks at 15 ms (range of the controls: 1-3-ms interval). This patient had a left unilateral lesion associated with a temporal resolution deficit. A similar deficit was found by Tanaka et al. (Albert & Bear, 1974; Tanaka et al., 1987). Their patient developed pure word deafness after bilateral temporoparietal lesions. She had no aphasia, but was unable to comprehend spoken words and also presented with expressive and receptive amusia. Threshold of click fusion was higher than in the patient reported by Auerbach et al. (1982). Slowing down speech did not improve auditory comprehension. The authors suggested that temporal resolution is not the only factor explaining pure word deafness; pitch, loudness, and tone duration are additional variables. Other studies have emphasized the relation between a deficit in the perception of rapid variations of acoustic stimuli and comprehension in dysphasic children. In a syllable identification task (/ba/ /da/) in which the length of formant transitions was varied (pairs of syllables with short—40 ms—and long—80 ms—transitions), Tallal and Piercy (1974) showed that languageimpaired children failed in the identification of syllables characterized by short formant transitions (such as /ba/ /da/). When the CV transitions were lengthened, identification was significantly better. It therefore seems to be the duration of the formant transition that affects discrimination of consonant stimuli in dysphasic children. A deficit in tone discrimination was found when ISI was very short. While the control group discriminated two tones with a 10-ms ISI, language-impaired children required an ISI of 150 ms to discriminate the two tones (Tallal & Piercy, 1973). The same pattern of impairment was found in a group of left-brain-damaged patients (Tallal & Newcombe, 1978), and the degree of impairment correlated with the degree of language comprehension impairment. These findings indicate that disruption of rapid temporal integration contributes to the phonological discrimination deficits in acquired and developmental aphasia. These results have therapeutic implications: several studies (Merzenich et al., 1996; Tallal et al., 1996) indicate that specific training may improve phonological discrimination as well as temporal integration rate. Aprosodia Prosody may be defined as a quality of speech that conveys meaning by variations of intonation, pitch, and duration. Prosody may therefore express the emotion of the speaker (happy, angry, or sad), but it may also indicate prepositional, nonemotional language content; that is, whether a sentence is a question or an affirmation. Distinction is therefore made between linguistic (nonaffective) prosody and emotional (affective) prosody. Deficit of affective and nonaffective prosody processing is called aprosodia, which has been observed in brain-damaged patients. Acquired aprosodia was also reported

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in children following congenital and focal brain injury (Bell, Davis, MorganFisher, & Ross, 1990). The most popular hypothesis suggests right-hemispheric dominance (RHD) for emotional prosody processing and left-hemispheric dominance (LHD) for linguistic prosody processing. Heilman, Bowers, Speedie, and Coslett (1984) found that RHD patients had impaired comprehension of emotional prosody compared to LHD group and normal controls. This finding corroborates previous studies on the role of the right hemisphere in emotional prosody comprehension (Heilman, Scholes, & Watson, 1975; Ross, 1981). The study of Heilman et al. (1984) highlighted yet another aspect of prosody processing: in a nonemotional prosody intonation task, where subjects had to point to the punctuation mark (? !) associated with a heard sentence, no hemispheric asymmetry was found. Thus, while the processing of emotional prosody seems to be represented in the right hemisphere, this is not the case for nonemotional prosody, which might rather be represented bilaterally. More recently, Ross, Thompson, and Yenkosky (1997) tested LHD and RHD patients and corroborated the idea that emotional prosody is lateralized in the right hemisphere. Few studies have tested the effects of early brain damage on prosody processing. Trauner, Ballantyne, Friedland, and Chase (1996) studied comprehension and expression of affective and linguistic prosody in children with unilateral pre- or perinatal brain damage and in age-matched controls. In expression tasks, both left- and right-brain-damaged patients were inferior to controls in affective and linguistic prosody tasks. Regarding comprehension, the authors found an impairment of affective prosody in the RHD group only. The latter finding concurs with right-hemisphere dominance for affective prosody in adults. However, as no laterality effect was found in expressive affective or linguistic prosody tasks, Trauner et al. (1996) suggest a bilateral representation for expressive affective and linguistic prosody during early development. Taken together, these findings agree with a right-brain lateralization for affective prosody comprehension that may be determined early during brain development. The right hemisphere is also involved in the processing of linguistic prosody, specifically the processing of sentence intonation (affirmative versus interrogative sentences). Aprosodia may also occur after left-hemisphere damage and then affect lexical accentuation. In sum, both hemispheres contribute differentially to the processing of specific prosody components. Phonagnosia The literature on neuropsychological impairments of voice recognition is scarce in comparison with prosopagnosia (face recognition deficit); phonagnosia has only recently been described (Van Lancker & Canter, 1982). The inability to recognize people by their voice or to discriminate between two

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voices represents a domain-specific form of agnosia, which dissociates from face recognition or name recognition. Furthermore, voice recognition frequently dissociates from speech recognition (Van Lancker, Kreiman, & Cummings, 1989). Assal, Aubert, and Buttet (1981) reported a patient who showed an impaired voice recognition that contrasted with preserved environmental sound recognition. Phonagnosia was associated in this case with a music perception deficit. This dissociation was subsequently described in two other studies (Neuner & Schweinberger, 2000; Peretz et al., 1994). Van Lancker and Canter (1982) described the opposite dissociation in two patients with impaired environmental sound recognition but normal recognition of familiar voices. Subsequent studies by the same authors (Van Lancker & Kreiman, 1987; Van Lancker, Cummings, Kreiman, & Dobkin, 1988; Van Lancker et al., 1989) indicated that familiar voice recognition and nonfamiliar voice discrimination constitute different capacities that anatomically dissociate. Familiar voice recognition deficit is associated with right parietal damage, whereas unfamiliar voice discrimination impairment is found after temporal lobe lesions without hemispheric preference. Neuroimaging data in healthy participants is partially compatible with lesion studies. Shah and colleagues (Shah et al., 2001) tested familiar and nonfamiliar voice perception in 10 normal controls. They did not find rightparietal activation as expected from lesions studies on recognition of famous voices (Van Lancker et al., 1989). Rather, they found bilateral activation on the superior temporal gyri with Heschl’s gyri for familiar and nonfamiliar voice perception. Similar bilateral temporal activation had been previously suggested in lesion studies on familiar voice identification (Imaizumi et al., 1997) and unfamiliar voice discrimination (Van Lancker et al., 1989). With respect to voice, an imaging study by Belin, Zatorre, Lafaille, Ahad, and Pike (2000) identified regions selectively activated by vocal sounds. Passive listening to vocal sounds (speech and nonspeech), as compared with nonvocal sounds listening, induced greater activation in the superior temporal sulcus bilaterally. Fecteau, Armony, Joanette, and Belin (2004) tested the hypothesis of a species-specific area for human vocalizations, as is the case for visual processing of human faces (George et al., 1999; Kanwisher, McDermott, & Chun, 1997; Leveroni et al., 2000). Normal participants’ brain activations were compared in an event-related fMRI design during listening to human vocalizations, animal’s vocalizations, and nonvocal sounds. Results showed evidence of stronger bilateral superior temporal sulcus activation for human vocalization than animal vocalizations and nonvocal sounds. This study suggests the existence of areas selective for human voice. Agnosia for nonverbal sounds—auditory agnosia Auditory agnosia for nonverbal material, which has been known since the end of the nineteenth century, is defined as the inability to recognize nonverbal sounds despite intact sound detection. It is mostly due to damage of the

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temporal lobe of the right or both hemispheres. Pure cases of agnosia for nonverbal sounds without evidence of agnosia for verbal sounds are rare. Distinct forms of nonverbal auditory agnosia exist, and different associations of deficits have been reported. Music processing may dissociate from environment sounds processing: Griffiths et al. (1997a) described a patient with a right-hemisphere lesion who had receptive amusia and deficient spatial sound analysis, whereas environmental sound recognition was normal. Environmental sounds Auditory perception impairments for nonverbal material have repeatedly been reported (Albert, Sparks, von Stockert, & Sax, 1972; Eustache, Lechevalier, Viader, & Lambert, 1990; Lambert et al., 1989; Motomura et al., 1986; Spreen et al., 1965). Spreen et al. (1965) described a right-handed patient with a right-temporal lesion who had normal speech comprehension, but who was severely impaired in identifying environmental sounds. Further investigation revealed that he had defective pitch, intensity, rhythm, and tempo discrimination, explaining also the associated receptive amusia. The existence of two forms of auditory agnosia was first discovered by Vignolo and colleagues (Faglioni, Spinnler, & Vignolo, 1969; Spinnler & Vignolo, 1966; Vignolo, 1982). They investigated the performance of a large group of unilateral right- and left-hemisphere damaged patients with the aim of studying the association between aphasia and auditory agnosia. The patients and the control group were evaluated in a sound-to-picture matching task, in which they had to point to one of four pictures with one corresponding to the target sound, one, an acoustic foil, one a semantic foil, and one an unrelated picture. Impaired sound recognition was frequently observed in aphasic patients and correlated with auditory comprehension impairments. A second important finding concerned the error types: aphasic participants mainly produced “semantic errors” (that is, they chose the foil belonging to the same semantic category as the sound), whereas right-hemisphere-damaged patients more often made acoustic errors (that is, they chose pictures representing acoustically related sounds). The authors concluded that auditory agnosia in aphasia qualitatively differs from auditory agnosia following right-hemisphere lesions. Left-hemisphere damage impairs the ability to associate a sound to its meaning (associative-semantic form), while right-hemisphere damage impairs discrimination of sounds (perceptualdiscriminative form). These findings have been confirmed in further studies. Eustache et al. (1990) reported the case of two patients with auditory agnosia. The first patient presented the associative form of auditory agnosia following left-hemisphere damage, while the second patient, with right-hemisphere damage, suffered from the perceptual-discriminative form of auditory agnosia. Schnider, Benson, Alexander, and Schnider-Klaus (1994) used a paradigm similar to that of Vignolo and colleagues and confirmed the results. Lesion analysis indicated

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that the qualitative right–left difference was much more pronounced after cortical than subcortical lesions. These findings are somewhat at odds with a study of Clarke, Bellmann, De Ribaupierre, and Assal (1996) testing semantic identification, asemantic recognition, and segregation of sound objects in controls and brain-damaged subjects. They observed a higher percentage of associative deficits (sound identity) in right-damaged patients than leftdamaged patients. Most studies reported auditory agnosia following bilateral cortical and subcortical lesions (Albert et al., 1972; Auerbach et al., 1982; Buchtel & Stewart, 1989; Kazui et al., 1990; Lechevalier et al., 1984; Lhermitte et al., 1971; Mendez & Geehan, 1988; Motomura et al., 1986; Oppenheimer & Newcombe, 1978; Vignolo, 1982). However, auditory agnosia was also described following unilateral left (Assal, 1973; Faglioni et al., 1969; Pasquier et al., 1991; Vignolo, 1982) or right lesions (Eustache et al., 1990; Faglioni et al., 1969; Fujii et al., 1990; Lechevalier, Eustache, & Rossa, 1985; Spreen et al., 1965; Vignolo, 1982). Functional imaging studies with normal individuals demonstrated left prefrontal, temporal, and parietal activations during tasks of environmental sounds categorization (Engelien et al., 1995). Maeder et al. (2001) found that sound recognition is processed within a network involving the anterior part of the middle temporal gyrus and the ventral part of the precuneus bilaterally and the left prefrontal cortex. Thus, the anatomical basis of sound recognition has been located in both hemispheres. Using fMRI, Adriani et al. (2003) tested sound recognition and auditory localization in right-hemispheredamaged patients, focusing on the left-hemisphere activation during these tasks. The authors noted that in patients with impaired performance in sound recognition and/or sound localization the level of activation in the left hemisphere was inferior and atypical, in comparison with the left activation found in patients with normal performance in sound recognition and localization. Thus, the results showed the influence of the right-hemispheric lesion on the contralateral processing within the auditory recognition and localization networks. Very few studies have investigated brain reorganization during recovery from auditory agnosia. Engelien et al. (1995) studied a patient (J.G.) who presented with auditory agnosia and word deafness (complete agnosia) after bilateral perisylvian strokes. Eight years later, the patient partially recovered from environmental sounds agnosia, but still had word deafness. The authors then used PET to study the mechanisms allowing recovery of environmental sounds categorization. Passive listening of environmental sounds was also scanned. In the control group, the authors found that passive listening to environmental sounds activated bitemporal areas, with more significant activation in the right hemisphere (Brodmann areas 41, 42, 22, and 39) and the posterior part of the thalamus bilaterally. In contrast, sound categorization only activated areas in the left hemisphere (dorsolateral prefrontal, middle temporal, inferior parietal, and anterior cingulate). This result was in accord

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with neuropsychological studies demonstrating left-hemisphere dominance of the associative type of auditory agnosia (Schnider et al., 1994; Spinnler & Vignolo, 1966). Unlike controls, the patient showed bilateral activation of a hemispheric network comprising prefrontal, middle temporal, and inferior parietal regions during sound categorization. The authors suggested that this bilateral activation was the basis of functional recovery. Pathophysiological and audiological studies suggested that impaired temporal order processing, loudness discrimination, auditory temporal resolution, and fusion threshold for clicks could be causally involved in auditory agnosia (Buchtel & Stewart, 1989; Jerger, Weikers, Sharbough, & Jerger, 1969; Kazui et al., 1990; Lambert et al., 1989; Motomura et al., 1986). Motomura et al. (1986) reported a patient with bilateral subcortical lesions and auditory agnosia who had abnormal performance in the threshold of clicks fusion and in loudness discrimination. Jerger et al. (1969) showed that patients with auditory agnosia may have difficulty in determining the temporal order of sounds or that they require increased sound intensity to discriminate stimuli. Auditory spatial perception impairment Localization of sounds in space may be impaired in isolation subsequent to cerebral damage. Auditory spatial processing appears to activate a distinct cortical network. Testing sound localization usually requires patients to point to the source of sounds delivered through loudspeakers or earphones. Clarke, Bellmann, Meuli, Assal, and Steck (2000) studied auditory recognition and spatial functions in four left-hemisphere-damaged patients. They found a double dissociation between sound recognition and localization. Two patients with a lesion to the left temporal convexity showed selective impairment in auditory recognition of sound meaning with normal performance in localization. Another patient with damage to the left inferior parietal and frontal convexities had a selective impairment of auditory-spatial capacities. These findings were recently confirmed by the same group (Clarke et al., 2002) when they studied 15 patients with right-hemispheric lesion and found a similar double dissociation. The authors suggest two anatomically distinct pathways for nonverbal auditory information: a ventral pathway comprising the temporal convexity involved in auditory recognition of sound identity (“what”), and a dorsal pathway comprising the parietal convexity and the insula contributing to auditory-spatial analysis (“where”). Recent fMRI and PET studies have supported the idea of anatomically distinct cortical networks involved in the processing of “what” and “where”. Using fMRI in healthy subjects, Maeder et al. (2001) found more bilateral activation in a network comprising prefrontal and posterior parietal cortices during sound localization than during sound recognition. Normal human functional imaging studies (fMRI and PET) suggested that processing of sound movement perception activates the right parietal cortex (Griffiths et al., 1998). This

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right-hemisphere involvement in auditory spatial perception is consistent with previous lesion studies (Griffiths et al., 1996). Music perception This topic is discussed in detail in Chapter 11 of this book and will only briefly be mentioned here. Amusia or music agnosia represents a distinct form of auditory agnosia, covering a variety of acquired impairments of musical processing following brain damage and congenital impairments of musical perception (Peretz & Hyde, 2002). In analogy to aphasia, expressive, receptive, and “global” amusia have been distinguished. Music agnosia may have a perceptual (apperceptive amusia) or a semantic basis (associative amusia), according to the two-stage processing model of music agnosia of Peretz et al. (1994). Associative amusia results from a deficit in accessing stored melodic representations while the ability to discriminate pitch and rhythm is normal. In contrast, apperceptive amusia results from an inability to process acoustic patterns of music perception. Griffiths et al. (1997b) described apperceptive music agnosia in a patient (H.V.) with a right unilateral lesion who showed impaired performance in tune recognition, contrasting with normal environmental sounds and prosody recognition. He was still able to sing from memory and to identify lyrics by their names. This impairment corresponded to pure apperceptive music agnosia. Other patients with apperceptive auditory agnosia had bilateral brain damage (Patel et al., 1998). Peretz et al. (1994) described two patients with bilateral damage who suffered from apperceptive auditory agnosia (impaired perception of tunes, voices, and prosody). PET studies in normal individuals have focused on pitch, timbre, and rhythm perception. Platel et al. (1997) observed right activation during a timbre task and left-hemispheric activation during pitch and rhythm processing tasks (left inferior Broca’s area and neighboring insula). Music perception appears to be mediated by different neural mechanisms than speech perception, as patients with selective impairment of music perception have been described. Studies of patients with brain damage suggest that the two primary dimensions of music—rhythm and melody—are processed by separate modules (Assal, 1973; Botez & Wertheim, 1959; Brust, 1980; Mavlov, 1980; Peretz, 1985). Wertheim and Botez (1961) described a professional violinist with a global music impairment following a lefthemispheric stroke, who completely failed to identify and imitate heard rhythms, but was markedly better at writing notes for rhythm than for pitch. Polk and Kertesz (1993) reported two musicians with probable Alzheimer’s disease. One patient with predominant left cortical atrophy had total loss of the ability to repeat simple acoustic rhythms but normal production of rhythms and intact melodic perception. The other patient with primarily right posterior cortical atrophy presented the reverse profile: he could repeat rhythms, but was unable to produce a regular rhythm. An important study on arrhythmia in a professional musician was reported by Mavlov (1980).

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Following a left posterior parietal lesion, a violinist and music teacher failed to discriminate and reproduce rhythmic patterns in the auditory, visual, and tactile modality. The rhythm impairment contrasted with a preserved ability to recognize and produce pitches. We reported on a professional baritone with left-temporoparietal stoke and receptive amusia (Di Pietro, Laganaro, Leemann, & Schnider, 2004). In a series of experiments, we found that the patient specifically had lost the ability to discriminate auditorily presented rhythms. In contrast, discrimination of visual rhythms was normal. His arrhythmia can therefore not be attributed to a supramodal temporal processing impairment. Our findings suggested modality-specific encoding of musical temporal information, and that the processing of auditory rhythmic sequences involves a specific left-hemispheric temporal buffer.

References Adriani, M., Maeder, P., Meuli, R., Thiran, A. B., Frischknecht, R., Villemure, J. G., et al. (2003). Sound recognition and localization in man: Specialized cortical networks and effects of acute circumscribed lesions. Experimental Brain Research, 153, 591–604. Albert, M., & Bear, D. (1974). Time to understand. A case study of word deafness with reference to the role of time in auditory comprehension. Brain, 97, 373–384. Albert, M. L., Sparks, R., von Stockert, T., & Sax, D. (1972). A case study of auditory agnosia: Linguistic and non-linguistic processing. Cortex, 8, 427–433. Assal, G. (1973). Aphasie de Wernicke sans amusie chez un pianiste. Revue Neurologique, 129, 251–256. Assal, G., Aubert, C., & Buttet, J. (1981). Asymétrie cérébrale et reconnaissance de la voix. Revue Neurologique, 137, 255–268. Auerbach, S. H., Allard, T., Naeser, M., Alexander, M. P., & Albert, M. L. (1982). Pure word deafness. Analysis of a case with bilateral lesions and a defect at the prephonemic level. Brain, 105, 271–300. Belin, P., Zatorre, R. J., Lafaille, P., Ahad, P., & Pike, B. (2000). Voice-selective areas in human auditory cortex. Nature, 403, 309–312. Bell, W. L., Davis, D. L., Morgan-Fisher, A., & Ross, E. D. (1990). Acquired aprosodia in children. Journal of Child Neurology, 5, 19–26. Botez, M. I., & Wertheim, N. (1959). Expressive aphasia and amusia following right frontal lesion in a right-handed man. Brain, 82, 186–203. Brust, J. C. (1980). Music and language: Musical alexia and agraphia. Brain, 103, 367–392. Buchtel, H. A., & Stewart, J. D. (1989). Auditory agnosia: Apperceptive or associative disorder? Brain and Language, 37, 12–25. Chocholle, R., Chedru, F., Bolte, M. C., Chain, F., & Lhermitte, F. (1975). Étude psychoacoustique d’un cas de “surdité corticale”. Neuropsychologia, 13, 163–172. Clarke, S., Bellmann, A., De Ribaupierre, F., & Assal, G. (1996). Non-verbal auditory recognition in normal subjects and brain-damaged patients: Evidence for parallel processing. Neuropsychologia, 34, 587–603. Clarke, S., Bellmann, A., Meuli, R. A., Assal, G., & Steck, A. J. (2000). Auditory

15. Auditory agnosia

279

agnosia and auditory spatial deficits following left hemispheric lesions: Evidence for distinct processing pathways. Neuropsychologia, 38, 797–807. Clarke, S. Bellmann Thiran, A., Maeder, P., Adriani, M., Vernet, O., Regli, L., et al. (2002). What and where in human audition: Selective deficits following focal hemispheric lesions. Experimental Brain Research, 147, 8–15. Coslett, H. B., Brashear, H. R., & Heilman, K. M. (1984). Pure word deafness after bilateral primary auditory cortex infarcts. Neurology, 34, 347–352. Denes, G., & Semenza, C. (1975). Auditory modality-specific anomia: Evidence from a case of pure word deafness. Cortex, 11, 401–411. Deonna, T., & Roulet, E. (1995). Acquired epileptic aphasia (AEA): Definition of the syndrome and current problems. In A. Beaumanoir, M. Bureau, T. Deonna, L. Mira, C. A. Tassinari (Eds.), Continuous spikes and waves during slow sleep (pp. 37–45). London: John Libbey. Deonna, T., & Zesiger, P. (1997). Syndrome d’aphasie acquise avec épilepsie chez l’enfant (Landau–Kleffner) et syndromes apparentés. In J. Lambert & J.-L. Nespoulous (Eds.), Perception auditive et compréhension (pp. 319–327). Marseille: Solal, Collection Neuropsychologie. Di Pietro, M., Laganaro, M., Leemann, B., & Schnider, A. (2004). Receptive amusia: Temporal auditory processing deficit in a professional musician following a left temporo-parietal lesion. Neuropsychologia, 42, 868–877. Ellis, A. W., Franklin, S., & Crerar, A. (1994). Cognitive neuropsychology and the remediation of disorders of spoken language. In M. S. Riddoch & G. W. Humphreys (Eds.), Cognitive neuropsychology and cognitive rehabilitation (pp. 287–315). Hove: Lawrence Erlbaum Associates Ltd. Engelien, A., Silbersweig, D., Stern, E., Huber, W., Doring, W., Firth, C., et al. (1995). The functional anatomy of recovery from auditory agnosia. A PET study of sound categorization in a neurological patient and normal controls. Brain, 118, 1395–1409. Eustache, F., Lechevalier, B., Viader, F., & Lambert, J. (1990). Identification and discrimination disorders in auditory perception: A report on two cases. Neuropsychologia, 28, 257–270. Faglioni, P., Spinnler, H., & Vignolo, L. A. (1969). Contrasting behavior of right and left hemisphere-damaged patients on a discriminative and a semantic task of auditory recognition. Cortex, 5, 366–389. Fecteau, S., Armony, J. L., Joanette, Y., & Belin, P. (2004). Is voice processing speciesspecific in human auditory cortex? An fMRI study. NeuroImage, 23, 840–848. Franklin, S., Howard, D., & Patterson, K. (1994). Abstract word meaning deafness. Cognitive Neuropsychology, 11, 1–34. Franklin, S., Turner, J., Lambon Ralph, M. A., Morris, J., & Bailey, P. J. (1996). A distinctive case of word meaning deafness? Cognitive Neuropsychology, 13, 1139–1162. Freud, S. (1891). Zur Auffassung der Aphasien. Wien: Deuticke. Fujii, T., Fukatsu, R., Watabe, S., Ohnuma, A., Teramura, K., Kimura, I., et al. (1990). Auditory sound agnosia without aphasia following a right temporal lobe lesion. Cortex, 26, 263–268. George, N., Dolan, R. J., Fink, G. R., Baylis, G. C., Russell, C., & Driver, J. (1999). Contrast polarity and face recognition in the human fusiform gyrus. Nature Neuroscience, 2, 574–580. Graham, J., Greenwood, R., & Lecky, B. (1980). Cortical deafness. A case report and review of the literature. Journal of the Neurological Sciences, 48, 35–49.

280

Di Pietro, Laganaro, Schnider

Griffiths, T. D. (2002). Central auditory pathologies. British Medical Bulletin, 63, 107–120. Griffiths, T. D., Bates, D., Rees, A., Witton, C., Gholkar, A., & Green, G. G. (1997a). Sound movement detection deficit due to a brainstem lesion. Journal of Neurology, Neurosurgery, and Psychiatry, 62, 522–526. Griffiths, T. D., Rees, A., Witton, C., Cross, P. M., Shakir, R. A., & Green, G. G. R. (1997b). Spatial and temporal auditory processing deficits following right hemisphere infarction. Brain, 120, 785–794. Griffiths, T. D., Rees, A., Witton, C., Shakir, R. A., Henning, G. B., & Green, G. G. (1996). Evidence for a sound movement area in the human cerebral cortex. Nature, 383, 425–427. Griffiths, T. D., Rees, G., Rees, A., Green, G. G., Witton, C., Rowe, D., et al. (1998). Right parietal cortex is involved in the perception of sound movement in humans. Nature Neuroscience, 1, 74–79. Heilman, K. M., Bowers, D., Speedie, L., & Coslett, H. B. (1984). Comprehension of affective and nonaffective prosody. Neurology, 34, 917–921. Heilman, K. M., Scholes, R., & Watson, R. T. (1975). Auditory affective agnosia. Disturbed comprehension of affective speech. Journal of Neurology, Neurosurgery, and Psychiatry, 38, 69–72. Imaizumi, S., Mori, K., Kiritani, S., Kawashima, R., Sugiura, M., Fukuda, H., et al. (1997). Vocal identification of speaker and emotion activates different brain regions. Neuroreport, 8, 2809–2812. Jerger, J., Weikers, N., Sharbough, F., & Jerger, S. (1969). Bilateral lesions of the temporal lobe: A case study. Acta Otolaryngologica, Supplement 285, 1–51. Kanwisher, N., McDermott, J., & Chun, M. M. (1997). The fusiform face area: A module in human extrastriate cortex specialized for face perception. Journal of Neuroscience, 17, 4301–4311. Kazui, S., Naritomi, H., Sawada, T., Inoue, N., & Okuda, J. (1990). Subcortical auditory agnosia. Brain and Language, 38, 476–487. Kussmaul, A. (1877). Disturbances of speech. In H. Von Ziemssen (Ed.), Cyclopedia of the practice of medicine (vol. 14, pp. 581–875). New York: William Wood. Lambert, J., Eustache, F., Lechevalier, B., Rossa, Y., & Viader, F. (1989). Auditory agnosia with relative sparing of speech perception. Cortex, 25, 71–82. Landau, W. M., & Kleffner, F. R. (1957). Syndrome of acquired aphasia with convulsive disorder in children. Neurology, 7, 523–530. Lechevalier, B., Eustache, F., & Rossa, Y. (1985). Les Troubles de la perception de la musique d’origine neurologique (vol. 1). Paris: Masson. Lechevalier, B., & Iglesias, S. (1997). Structures anatomiques de la perception auditive (bruits, langage, musique). In J. Lambert & J.-L. Nespoulous (Eds.), Perception auditive et compréhension. État initial, état stable et pathologies (pp. 73–83). Marseille: Collection Neuropsychologie. Lechevalier, B., Rossa, Y., Eustache, F., Schupp, C., Boner, L., & Bazin, C. (1984). Un cas de surdité corticale épargnant en partie la musique. Revue Neurologique, 140, 190–201. Leveroni, C. L., Seidenberg, M., Mayer, A. R., Mead, L. A., Binder, J. R., & Rao, S. M. (2000). Neural systems underlying the recognition of familiar and newly learned faces. Journal of Neuroscience, 20, 878–886. Lhermitte, F., Chain, F., Escourolle, R., Ducarne, B., Pillon, B., & Chedru, F. (1971).

15. Auditory agnosia

281

Étude des troubles perceptifs auditifs dans les lésions temporales bilatérales. Revue Neurologique, 124, 329–351. Lichtheim, L. (1885). On aphasia. Brain, 7, 433–484. Maeder, P. P., Meuli, R. A., Adriani, M., Bellmann, A., Fornari, E., Thiran, J. P., et al. (2001). Distinct pathways involved in sound recognition and localization: A human fMRI study. NeuroImage, 14, 802–816. Mavlov, L. (1980). Amusia due to rhythm agnosia in a musician with left hemisphere damage: A non-auditory supramodal defect. Cortex, 16, 331–338. Mendez, M. F., & Geehan, G. R. (1988). Cortical auditory disorders: Clinical and psychoacoustic features. Journal of Neurology, Neurosurgery, and Psychiatry, 51, 1–9. Merzenich, M., Jenkins, W., Johnston, P. S., Schreiner, C., Miller, S. L., & Tallal, P. (1996). Temporal processing deficits of language-learning impaired children ameliorated by training. Science, 271, 77–80. Metz-Lutz, N. M., de Saint Martin, A., Hirsch, E., Maquet, P., & Maresceaux, C. (1999). Impairment in auditory verbal processing and dichotic listening after recovery of epilepsy in Landau and Kleffner syndrome. Brain and Cognition, 40, 193–197. Michel, F., & Peronnet, F. (1980). A case of cortical deafness: Clinical and electrophysiological data. Brain and Language, 10, 367–377. Motomura, N., Yamadori, A., Mori, E., & Tamaru, F. (1986). Auditory agnosia. Analysis of a case with bilateral subcortial lesions. Brain, 109, 379–391. Neuner, F., & Schweinberger, S. R. (2000). Neuropsychological impairments in the recognition of faces, voices, and personal names. Brain and Cognition, 44, 342–366. Oppenheimer, D. R., & Newcombe, F. (1978). Clinical and anatomic findings in a case of auditory agnosia. Archives of Neurology, 35, 712–719. Pasquier, F., Leys, D., Steinling, M., Guieu, J. D., Petit, H., & Cambier, J. (1991). Agnosie auditive unilatérale droite consécutive à une hémorragie lenticulaire gauche. Revue Neurologique, 147, 129–137. Patel, A. D., Peretz, I., Tramo, M., & Labreque, R. (1998). Processing prosodic and musical patterns: A neuropsychological investigation. Brain and Language, 61, 123–144. Peretz, I. (1985). Asymétrie hémisphérique dans les amusies. Revue Neurologique, 141, 169–183. Peretz, I., & Hyde, K. (2002). Congenital amusia: A disorder of fine-grained pitch discrimination. Brain, 125, 238–251. Peretz, I., Kolinsky, R., Tramo, M., Labrecque, R., Hublet, C., Demeurisse, G., et al. (1994). Functional dissociations following bilateral lesions of auditory cortex. Brain, 117, 1283–1301. Pinard, M., Chertkow, H., Black, S., & Peretz, I. (2002). A case study of pure word deafness: Modularity in auditory processing? Neurocase, 8, 40–55. Platel, H., Price, C., Baron, J.-C., Wise, R., Lambert, J., Frackowiak, R. S. J., et al. (1997). The structural components of music perception. A functional anatomical study. Brain, 120, 229–243. Polk, M., & Kertesz, A. (1993). Music and language in degenerative disease of the brain. Brain and Cognition, 22, 98–117. Polster, M. R., & Rose, S. B. (1998). Disorders of auditory processing: Evidence for modularity in audition. Cortex, 34, 47–65. Ross, E. (1981). The aprosodias. Functional-anatomic organization of the affective components of language in the right hemisphere. Archives of Neurology, 38, 561–569.

282

Di Pietro, Laganaro, Schnider

Ross, E. D., Thompson, R. D., & Yenkosky, J. (1997). Lateralization of affective prosody in brain and the callosal integration of hemispheric language functions. Brain and Language, 56, 27–54. Saffran, E. M., Marin, O., & Yeni-Komshan, G. (1976). An analysis of speech perception in word deafness. Brain and Language, 3, 209–228. Schnider, A., Benson, D. F., Alexander, D. N., & Schnider-Klaus, A. (1994). Nonverbal environmental sound recognition after unilateral hemispheric stroke. Brain, 117, 281–287. Shah, N. J., Marshall, J. C., Zafiris, O., Schwab, A., Zilles, K., Markowitsch, H. J., et al. (2001). The neural correlates of person familiarity. A functional magnetic resonance imaging study with clinical implications. Brain, 124, 804–815. Spinnler, H., & Vignolo, L. A. (1966). Impaired recognition of meaningful sounds in aphasia. Cortex, 2, 337–348. Spreen, O., Benton, A. L., & Fincham, R. W. (1965). Auditory agnosia without aphasia. Archives of Neurology, 13, 84–92. Tallal, P., Miller, S. L., Bedi, G., Byma, G., Wang, X., Nagarajan, S. S., et al. (1996). Language comprehension in language-learning impaired children improved with acoustically modified speech. Science, 271, 81–84. Tallal, P., & Newcombe, F. (1978). Impairment of auditory perception and language comprehension in dysphasia. Brain and Language, 5, 13–24. Tallal, P., & Piercy, M. (1973). Defects of non-verbal auditory perception in children with developmental aphasia. Nature, 241, 468–469. Tallal, P., & Piercy, M. (1974). Developmental aphasia: Rate of auditory processing and selective impairment of consonant perception. Neuropsychologia, 12, 83–93. Tanaka, Y., Kamo, T., Yoshida, M., & Yamadori, A. (1991). “So-called” cortical deafness. Clinical, neurophysiological and radiological observations. Brain, 114, 2385–2401. Tanaka, Y., Yamadori, A., & Mori, E. (1987). Pure word deafness following bilateral lesions. A psychophysical analysis. Brain, 110, 381–403. Trauner, D. A., Ballantyne, A., Friedland, S., & Chase, C. (1996). Disorders of affective and linguistic prosody in children after early unilateral brain damage. Annals of Neurology, 39, 361–367. Van Lancker, D., & Kreiman, J. (1987). Voice discrimination and recognition are separate abilities. Neuropsychologia, 25, 829–834. Van Lancker, D. R., & Canter, G. J. (1982). Impairment of voice and face recognition in patients with hemispheric damage. Brain and Cognition, 1, 185–195. Van Lancker, D. R., Cummings, J. L., Kreiman, J., & Dobkin, B. H. (1988). Phonagnosia: A dissociation between familiar and unfamiliar voices. Cortex, 24, 195–209. Van Lancker, D. R., Kreiman, J., & Cummings, J. (1989). Voice perception deficits: Neuroanatomical correlates of phonagnosia. Journal of Clinical and Experimental Neuropsychology: Official Journal of the International Neuropsychological Society, 11, 665–674. Vignolo, L. A. (1982). Auditory agnosia. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 298, 49–57. Wang, E., Peach, R. K., Xu, Y., Schneck, M., & Manry, C. (2000). Perception of dynamic acoustic patterns by an individual with unilateral verbal auditory agnosia. Brain and Language, 73, 442–455. Wernicke, K., & Friedländer, C. (1893). A case of deafness as a result of bilateral

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lesions of the temporal lobe. In G. H. Eggert (Ed.), Wernicke’s works on aphasia (pp. 164–172). New York: Mouton. Wertheim, N., & Botez, M. I. (1961). Receptive amusia: A clinical analysis. Brain, 84, 19–30.

16 Somaesthetic recognition disorders Gabriella Bottini and Martina Gandola

In everyday life, the manipulation of objects may occur also in the absence of visual input (as in looking for something in our pocket or handbag). This common operation involves many cognitive processes from the more elementary levels (touch, pressure, proprioception, etc.) to higher levels, allowing us to build up a complete object image. The complexity of the somatosensory neural system justifies the large variability of symptoms presented by subjects suffering from tactile recognition disorders. At the clinical level, it is possible to distinguish between low, elementary defects such as hemianaesthesia, which is typically related to a lesion in the contralateral somatosensory cortex, and higher, more “cognitive” disorders such as tactile agnosia, that is, a deficit in recognizing the meaning of a tactually explored object. In this chapter, we review the anatomical and functional organization of the somatosensory system, and provide information from functional neuroimaging evidence. We then review the clinical and theoretical issues of higher somatosensory disorders.

Anatomical organization of the somatosensory system Natural stimuli generally activate many different receptors, with the consequent production of numerous specific sensations (touch, pain, thermal sense, wetness, perception of the position of the limb, and sense of movement). Tactile signals from the body travel through peripheral nerves to the dorsal root ganglia, where the first-order sensory neurons are located. From this first step, signals are sent along the dorsal columns of the spinal cord, whose axons synapse with the cells of the dorsal nuclei (gracile and cuneate nuclei) in the medulla oblongata, where second-order sensory neurons of the dorsal column system are located. Ascending projections arrive from these cells, through the medial lemniscal system to the ventral posterior nuclei of the thalamus. The thalamus is the principal relay station for sensory stimuli. Somatic sensation is mediated by the ventral posterior nuclear complex (VP), which is subdivided into a number of components: the ventro-postero-medial (VPM) nucleus, the ventro-postero-lateral nucleus (VPL), the ventro-posteroinferior (VPI) nucleus, and the ventro-postero-superior (VPS) nucleus. The

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VPM nucleus receives cutaneous inputs from the face, while the VPL receives inputs from the rest of the body. At this level, precise somatotopic organization takes place (Poggio & Mountcastle, 1963). The VPS nucleus receives deep tissue inputs. The role of the VPI is not yet well understood. It has been suggested that, in primates, the VPI may be of functional importance, because it is the major relay nucleus projecting to the second somatosensory areas (Friedman & Murray, 1986). From the thalamus, the somatosensory signals finally arrive at the anterior parietal cortex, through the internal capsule. It is important to note that, before further integration, these signals are kept somewhat segregated from the periphery up to the primary somatosensory cortical areas. The major cortical areas of the monkey brain with prevalent somatosensory function, and their human homologues, are the primary somatosensory complex (Brodmann areas 3a, 3b, 1, and 2), area 5, area 7b, the second somatosensory area (SII), the granular insula (Ig), and the retroinsular cortex (area Ri). The primary somatosensory cortex (SI) SI is located in the bank of the central sulcus (areas 3a and 3b) and on the surface of the postcentral gyrus (areas 1 and 2) in the parietal lobe. Each of these four regions contains independent and complete representations of the contralateral body surface (Kaas, 1983; Kaas, Nelson, Sur, Lin, & Merzenich, 1979; Merzenich, Kaas, Sur, & Lin, 1978). As there is a segregation of the sensory signals from the periphery to the cortex, it is important to note that each of the above maps represents different somatosensory receptors. Areas 3b and 1 have two mirror-reversed body maps of cutaneous receptors, while areas 2 and 3a primarily respond to the deep stimulation of joints (area 2) and muscles (area 3a), in accordance with the classification of Brodmann (1909) and Vogt and Vogt (1919). Electrical stimulation of SI surface induces somatic sensations in relation to specific body parts. This kind of exploration was adopted for the first time by Penfield and colleagues (Penfield & Jasper, 1954), who studied awake epilepsy patients and provided the first cortical maps of the human body representation in the somatosensory cortex (homunculus sensitivus). The somatotopy of these areas corresponds to the well-known superomesial (tailfoot) and lateroventral (tongue) arrangement. Hence, the inferior limbs are represented at the vertex, with the foot on the mesial wall of the postcentral gyrus, while the upper limbs and mouth are represented on the convexity, with the mouth area, tongue, and larynx at the bottom of the gyrus. Furthermore, there is a disproportionately larger representation of the hand and mouth areas than those of the trunk.

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The secondary somatosensory cortex (SII) In the monkey, this area is located in the upper, parietal bank of the lateral sulcus, behind the insula (Burton, 1986; Robinson & Burton, 1980b). There is a clear cytoarchitectonic difference between SI and SII. SII contains a whole body map with a quite accurate representation of the body segments (Burton, 1986; Robinson & Burton, 1980a). The face is represented in the anterolateral portion of SII and the tail (foot) in the posteromedial portion. In the neural population of SII, nearly 40% of cells have bilateral receptive fields (RFs), suggesting that the area may have associative functions. Through electrical stimulation, Penfield and co-workers (Penfield & Jasper, 1954; Penfield & Rasmussen, 1950) identified human SII location on the convexity near the sylvian fissure and below the central sulcus. Other somatosensory areas Retroinsula and postauditory areas Neurons responding to touch have also been identified in the retroinsular (Ri) and postauditory (Pa) cortices (Robinson & Burton, 1980a, 1980b). RFs in Ri neurons are very similar to those of SII. There is no clear evidence of the somatotopic arrangement of these two areas, while an anteroposterior gradient, similar to that in SII, has been proposed for Ri (Robinson & Burton, 1980a, 1980b). Insula It is now well known that the insula has a function not only in monitoring visceral signals (Mesulam & Mufson, 1982, 1986; Mufson, Mesulam, & Pandya, 1981). The granular insula in particular has an important role in processing somatic sensation. Posterior parietal cortex: Brodmann areas 7 and 5 Monkey area 7 is divided into anterior area 7b and posterior area 7a. Only area 7b has somatic properties (Hyvarinen, 1982; Kaas, 1990). It is difficult to establish the human homologues of these monkey areas. It has been proposed that the human homologue of monkey BA5 corresponds to human BA5 and BA7, while human BA40, in the supramarginal gyrus, corresponds to the anterior part of the monkey area (Hyvarinen, 1982). In the monkey, area 7b is involved in high-order integration within the somatosensory system. Most neurons in this area have bilateral RFs and contain a crude body map according to the mainly associative role of 7b (Hyvarinen, 1982).

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How functional neuroimaging contributes to knowledge of the anatomy and functions of the somatosensory complex In this section, we shall provide information about tactile perception and shall not investigate other sensations such as pain, and visceral and vestibular signals. Functional neuroimaging studies have explored, albeit not systematically, the different functions of the somatosensory areas (Burton, Videen, & Raichle, 1993; Coghill et al., 1994; Fox, Burton, & Raichle, 1987; Seitz & Roland, 1992). Although most studies have investigated the more elementary processing (such as touch perception and vibration), a number of quite recent experiments have also investigated higher somatosensory processing such as object recognition. SI SI activation can be easily detected after vibratory stimulation or during sensory-motor tasks (Burton et al., 1993; Coghill et al., 1994; Colebatch, Deiber, Passingham, Friston, & Frackowiak, 1991; Fox et al., 1987; Grafton, Woods, & Mazziotta, 1993; Rao et al., 1995; Remy, Zilbovicius, Leroy-Willig, Syrota, & Samson, 1994; Seitz & Roland, 1992). However, greater difficulty is encountered in detecting significant activation when purer stimuli are applied, such as suprathreshold electrical cutaneous stimulation or suprathreshold touches via a von Frey hair (Burton et al., 1993). In primates, vibratory stimuli, although delivered unilaterally, induce bilateral activation of the somatosensory complex (Burton et al., 1993). Neuroimaging studies in man exploring SI activation during sensory-motor tasks have demonstrated bilateral activation of this area (Colebatch et al., 1991), suggesting the following features: (1) descending ipsilateral corticospinal fibre activity, (2) bilateral receptive fields in the somatosensory complex, and (3) transcallosal projections from the contralateral somatosensory complex. Somatotopic organization of the somatosensory complex has also been explored by a number of activation studies. Under 3–5 Hz pressure stimulation, for example, a bilateral putative SII activation has been revealed in agreement with previous demonstration by Penfield and Rasmussen (1950) during cortical electrostimulation. However a somatotopic organization of the hand and foot has only been shown for SI (Moore, Gehi, Guimereas, Corkin, Rosen, & Stern, 1966). As already mentioned, it is generally difficult to activate the somatosensory complex by pure sensory stimulations. On the other hand, few experiments have shown that pure tactile stimulation may induce activation in motor areas. This phenomenon was called by Ingvar (1975) the sensory motor paradox and has been replicated by other authors (Pardo, Fox, & Raichle, 1991; Paulesu, Frackowiak, & Bottini, 1997). There are different explanations of this paradox: one is that SI responds only to specific kinds of stimuli.

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SII There is contradictory information about SII functions from the in vivo observations of different authors (Luders, Lesser, Dinner, Hahn, Salanga, & Morris, 1985; Penfield & Jasper, 1954). Furthermore, it is difficult to make a clear comparison with primate SII. Comparative studies have, in fact, been performed at the micro- or macroanatomical level or have mainly explored SII functioning. Recently, some functional magnetic resonance imaging (fMRI) activation studies in man have aimed at clarifying the organization of SII, identifying, for example, the regions in the lateral sulcus and their topographic organization, in order to compare the human somatosensory complex with that of other primates and other mammals. Disbrow, Roberts, and Krubitzer (2000), for example, provided evidence of four fields in the lateral sulcus, with good similarity to previous studies performed with analogous kinds of stimulation (Burton et al., 1993; Coghill et al., 1994; Gelnar, Krauss, Szeverenyi, & Apkarian, 1998). On the other hand, there is no general agreement on the topographical arrangement. This divergence might depend on the different instruments used in the experiments, since positron emission tomography (PET) (Burton et al., 1993) provides less accurate anatomical details than fMRI (Disbrow et al., 2000; Ruben et al., 2001). Another explanation could be found in the diverse paradigms adopted: the fewer the stimulated body segments, the smaller the chance to find a somatotopic organization of putative human SII. Considering the degree of bilateral hemispheric activation, a relevant amount of variability seems, once again, to be related to the kind of stimulation. By comparing putative human SII with the same region in other primates and mammals, it is possible to identify some similarities at the neuronal level, showing, for example, bilateral receptive fields (Disbrow et al., 2000). What about higher somaesthetic recognition functions? Neuroimaging studies in this field adopted paradigms mainly characterized by the identification of meaningless objects. Some of them compared these kinds of stimuli with meaningful objects that had to be named. Binkofski, Buccino, Stephan, Rizzolatti, Seitz, and Freund (1999) aimed to identify brain areas active during the manipulation of complex objects. In one experiment, subjects were required to manipulate complex objects to explore their macrogeometric features, as compared to the manipulation of a simple, smooth object. In a second experiment, subjects were asked to manipulate complex objects and silently name them upon recognition, as compared to manipulation of complex, not recognizable objects without covert naming. The authors found that manipulation of complex objects induces activation of the ventral premotor cortex, of a region in the intraparietal sulcus, of area SII, and of a sector of the superior parietal lobule. When the objects were covertly named, additional activations were found in the opercular part of

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BA 44 and in the pars triangularis of the inferior frontal gyrus (BA 45). The authors suggest that a frontoparietal circuit for the manipulation of objects exists in man, basically involving the same areas as in the monkey (Binkofski et al., 1999). In order to isolate higher tactile recognition, intended as the naturalistic tactile object recognition of real objects, another fMRI study (Reed, Shoham, & Halgren, 2004) compared this task with a task of palpation of “nonsense” stimuli and with rest. Compared to nonsense object palpation, the most prominent activation evoked by tactile object recognition was in secondary somatosensory areas in the parietal operculum (SII) and insula, confirming a modality-specific path for this process. Prominent activation was also present in medial and lateral secondary motor cortices, but not in primary motor areas, supporting the high level of sensory and motor integration characteristic of object recognition in the tactile modality. This study confirms the involvement of somatosensory association areas in the recognition component of tactile object recognition, and the existence of a ventrolateral somatosensory pathway for this process in normal subjects (Reed et al., 2004). Tactile object recognition has a dual nature, as it comprehends hand manipulation (low-level sensory motor process) aimed to identify the object itself (high conceptual level). These processes have been explored in a fMRI study on normal subjects with the following tasks: (1) manually exploring three-dimensional plasticine objects to understand their shape, (2) imagining to construct the previous explored stimuli, and (3) constructing these objects by manipulating plasticine. These different tasks induce activation in a number of motor, associative, and somatosensory regions. The most relevant results are that both constructing and exploring activate the posterior and anterior intraparietal sulcus bilaterally. The imagining condition activates beyond the left posterior intraparietal sulcus, the ventropremotor area slightly above Broca’s area. These findings, together with the above-mentioned evidence (Binkofski et al., 1999), demonstrate a contiguity between the neural systems controlling the manipulative behaviour and language (Jancke, Kleinschmidt, Mirzazade, Shah, & Freund, 2001).

Classification of recognition disorders: from elementary deficits to tactile agnosia The complexity of the somatosensory system is also reflected by the numerous symptoms that can be hierarchically classified from elementary to higherorder tactile recognition deficits (Figure 16.1). This section will illustrate, in particular, tactile deficits, and not pain and visceral perception impairments. Human brain lesions are not restricted to one cytoarchitectonic field in the postcentral somatosensory complex. Thus, classical postcentral damage induces several deficits of different skills such as pressure sensitivity, two-point discrimination, and identification of object

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Figure 16.1 Somatosensory disorders: from the elementary to the high-level impairments.

shape, size, and texture. Compared with these deficits, more elementary symptoms, such as insensitivity to pain, vibration, touch, and temperature change, are significantly less common. They may occur in subjects with a quite extensive lesion of SI, while preserving all or at least part of SII, which may compensate for the elementary somatosensory functions (Roland, 1987). Disorders of tactile perception The high anatomical complexity of the somatosensory system accounts for the analogous complexity of the series of deficits derived from lesions of different areas of this system. Thus, somatosensory deficits may be hierarchically classified from the more elementary to high-level impairments depending on the side, extension, and region involved in cerebral damage. While ablation of the visual and auditory primary cortices induces complete lack of these two sensory modalities, somaesthetic deficits are rarely associated with cortical lesion (Hécaen & Albert, 1978). This difference is to be ascribed to the redundancy of the somatosensory system, which guarantees a certain functional compensation even in the presence of quite extensive cerebral damage. Furthermore, in everyday life, higher somaesthetic complex functions, such as object recognition, derive from the integration of many

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different components allowing perception of temperature, shape, texture, pressure, etc. As a consequence, in the case of brain damage, it is extremely difficult to isolate the level of the stimulus analysis at which the deficit occurs. von Frey (1895) was the first to propose a division of sensory functions. Subsequently, different clinical symptom classifications have been suggested (Head, 1918). Hemianaesthesia or tactile imperception is the inability to perceive touch in the half of the body contralateral to the side of brain injury (anterior parietal lobe syndrome). Although this symptom is classically recognized as an elementary impairment, there is some evidence that this deficit may involve a cognitive component as well. Right-sided brain injuries, for example, are associated with a greater incidence of contralateral hemianaesthesia, as demonstrated by a retrospective study on a quite large population of stroke patients (Sterzi et al., 1993). On the basis of the well-known asymmetry according to which unilateral neglect occurs much more frequently after a right hemispheric lesion, one may speculate that left-body tactile imperception can be explained as a mild form of personal neglect. The cognitive component of hemianaesthesia may also be inferred by the transient remission of this deficit during caloric vestibular stimulation (Vallar, Bottini, Rusconi, & Sterzi, 1993; Vallar, Sterzi, Bottini, Cappa, & Rusconi, 1990). In order to introduce higher-level somatosensory disorders, we will first present the cognitive processes subserving complex stimuli (objects) identification and recognition. Tactile object recognition (TOR) This section does not aim to provide a detailed illustration of the different models of TOR; rather, it will elaborate on the most relevant theoretical issues still open to debate. The apperceptive and the associative levels In 1890, Lissauer (1890) was the first to introduce the dichotomy between apperceptive and associative levels in recognition. He divided the recognition process into two stages: (1) “the stage of conscious awareness of a sensory impression”, entailing the analysis of the physical features of the stimulus (apperceptive stage), and (2) “the stage of associating other notions with the contents of this apperception”, providing a linkage between the percept and its meaning (associative stage). Lissauer divided agnosia into two basic forms: apperceptive agnosia, which prevents object recognition because of inability to form stable representations of percept, and associative agnosia, which induces inability to attribute meaning to the object, thus preventing its identification. A deficit of the apperceptive level is associated with lesions of the right hemisphere, while dysfunction of the associative level is related to lefthemispheric damage. This distinction suggests that TOR involves a kind of

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serial model, first providing tactile perception and secondly the labelling of the recognized object. Although seminal, the Lissauer model is now widely questioned. Much behavioural evidence of TOR from both brain-damaged patients and normal controls cannot be explained solely in terms of the Lissauer theory. More hard-wired models are formulated in neural terminology, such as the model proposed by Damasio (1989), who suggests that perception involves the evocation of a neural activity pattern in primary and first-order association cortices, which correspond to the various perceptual features extracted from the viewed object. This model suggests that there is no fundamental distinction between perception and memory. Information about known objects is not stored in a localized representation but is distributed in a neural system. Other authors have tried to relate the cognitive organization of object recognition to specific cerebral areas (Endo, Miyasaka, Makishita, Yanagisawa, & Sugishita, 1992; Nakamura, Endo, Sumida, & Hasegawa, 1998; Platz, 1996). Outstanding questions In general, most models of object recognition imply a strong connection between different sensory modalities and semantic memory, and assume the existence of both the apperceptive and the associative levels. Nevertheless, these models differ from each other in several respects. There are two fundamental issues. The first is whether each sensory modality is subserved by a specific semantic memory, or whether all sensory modalities refer to a general semantic thesaurus (Endo et al., 1992; Nakamura et al., 1998; Platz, 1996). The second problematic aspect of object recognition models, whatever the sensory modality, is whether the apperceptive and the associative levels must be assumed to be organized in a serial or in a parallel fashion. This problem in particular will be debated below (Rudge & Warrington, 1991; Warrington & Taylor, 1978).

Tactile agnosia: theoretical and clinical issues Tactile agnosia is the inability to recognize tactually presented objects in the absence of any elementary sensory (ahyloagnosia or amorphoagnosis), attentional, intellectual, and linguistic deficits (Bauer, 1993). Delay (1935) postulated three different mechanisms involved in object recognition. He distinguished between two forms of primary tactile disturbance: (1) “ahyloagnosia”, characterized as impairment of the capacity to appreciate the “intensity” of tactile stimuli, such as density, weight, texture, and thermal properties, and (2) “amorphoagnosis”, characterized as failure to recognize the “extension qualities” of an object such as size and shape. A third type of agnosia, classified as a secondary identification deficit, is tactile agnosia or tactile asymbolia. In this last case, there is a failure to recognize the meaning

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of a stimulus in the absence of ahyloagnosia and amorphoagnosis. Wernicke (1895) had already distinguished between primary tactile agnosia, due to impairment in the “tactile images”, characterized by inability to describe the physical qualities of objects (dimension, form, texture, etc.), and a secondary identification deficit, tactile asymbolia, related to a disconnection between the centre of “tactile images” and the centre of the other sensory representations. The patient cannot understand the “meaning” of objects through the tactile modality, although the ability to recognize the tactile qualities of objects is preserved (Wernicke, 1895). Why is tactile agnosia identification so difficult? Tactile agnosia and primary sensory deficits The existence of “pure” tactile agnosia, without the concomitant presence of primary somatosensory deficits, has been greatly debated. Indeed, only a few cases of tactile agnosia without concomitant sensory or higher-order perceptual deficits have been reported. Various authors suggest that a pure form of tactile agnosia does not exist and that the reported cases of tactile agnosia may be explained by the concomitant presence of light, elementary somatosensory dysfunctions. As early as 1911, Head and Holmes (1911) proposed that an object identification defect derives from the coexistence of more elementary symptoms, such as the instability of the sensory threshold. Bay (1944) also denied the existence of tactile agnosia and claimed that many patients described in the literature had mild impairments of sensory discrimination with consequent lability of the somatosensory threshold when performing somatosensory tasks. This hypothesis seems to be supported by the strong evidence provided by the study of Corkin, Milner, and Rasmussen (1970). They explored the somatosensory functions of epileptic patients who had undergone localized ablation of the epileptogenic zone. The patients’ elementary sensory functions and tactile object-recognition abilities were both explored. Only in subjects who had postcentral gyrus exeresis was performance pathological, and all of them also presented basic sensory deficits, such as in stimuli thresholding and localization, two-point discrimination, and position sense. Further evidence in this direction was also provided by Roland (Roland & Larsen, 1976). However, conflicting opinions derive from the fact that these subtle sensory deficits cannot always explain a remarkable deficit, such as object misidentification. Caselli (1991) tried to clarify this conflict by systematically investigating 84 brain-damaged patients with an extensive battery of tests on the somatosensory function. Basic (assessment of touch, pain, temperature, vibration, kinaesthesia, proprioception, and two-point discrimination) and intermediate (standard clinical assessment and quantitative measurements of perception of weight, texture, dimension, shape, and substance) somatosensory functions and tactile object recognition were tested. The object-recognition

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task was performed in both somatosensory and visual modalities. The author described several patients with pure tactile object-recognition deficit. These patients had impairment of somaesthetically mediated object recognition that could not be explained by the coexistence of more basic or intermediate types of somatosensory imperception, failure to explore objects, or failure to communicate the identity of objects. This type of deficit occurs after focal unilateral damage in the right or left hemisphere, involving the parietotemporal cortices, possibly including the SII or the surrounding parietotemporal and posterior insular cortices (Caselli, 1991). In conclusion, the historical literature on this topic presents different points of view. However, there is general agreement that, although elementary sensory deficits coexist, the impairment of object recognition represents a quite distinctive higher-cognitive dysfunction. Tactile agnosia and coexistent higher-cognitive deficits Defining tactile agnosia as a pure, independent deficit is often very difficult, as other complex cognitive syndromes may mediate this symptom. Among them are tactile aphasia or anomia and supramodal spatial deficits such as unilateral neglect. Tactile anomia is the inability to name or describe an object explored through the somatosensory modality (Beauvois, Saillant, Meininger, & Lhermitte, 1978; Endo et al., 1992), in the absence of somaesthetic dysfunction. In this way, tactile aphasia differs from tactile agnosia, which is a specific impairment of object recognition, and not of object naming. Patients suffering from tactile anomia can recognize the object by touching it and can also demonstrate that they have recognized the stimulus, in a non-verbal fashion. Therefore, this deficit represents the consequence of a disconnection between tactile-recognition mechanisms and speech processing (naming). Although the boundary between these two deficits seems to be controversial, in recent years a number of studies have quite consistently proven the existence of tactile agnosia. Indeed, few cases of pure tactile agnosia have been reported (Caselli, 1991; Endo et al., 1992; Platz, 1996). Endo et al. (1992) described some cases of brain-damaged subjects, in order to demonstrate that tactile agnosia and tactile aphasia have different pathogenesis and anatomopathological substrates. They administered patients an extensive battery of tests exploring their ability to differentiate weight, texture, and materials of tactually presented objects (hylognosis), and to discriminate between two- and three-dimensional figures (morphognosis). Subsequently, the ability to name objects presented tactually and to categorize them was explored. On the basis of this assessment, they concluded that one patient showing normal hylognosis and morphognosis, but inability to categorize tactually and name stimuli, was suffering from tactile agnosia, while a second patient who could not name objects, but was able to categorize them, presented tactile aphasia. Based on this neuropsychological evidence, the

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authors proposed a model in which the tactile exploration of an object activates somatosensory receptors and the information is sent to a register of somatosensory stimuli. The information arrives in the somatosensory shortterm memory system (STM), where it is compared with past memories of already palpated objects, retrieved from the somatosensory long-term memory (LTM). The intervention of memory allows a comparison mechanism that is the basis of hylognosis and morphognosis, as it allows comparison of new stimuli with stored stimuli with specific shape and texture. The information about material and form is then matched with the conceptual information retrieved from semantic memory. This stage corresponds to complete object recognition. The labelling process of the object (verbalization) derives from the direct connection between semantic and lexical memory. According to this model, tactile agnosia occurs when access from the STM to the semantic memory is interrupted, while tactile aphasia occurs when retrieved semantic memory is not transmitted to lexical memory (impaired verbalization). On the basis of CT scan evidence on the cerebral lesions of their patients, the authors suggest that tactile agnosia is related to a disconnection between the somatosensory cortex and the semantic memory store in the inferior temporal lobe due to a subcortical lesion of the angular gyrus. When cerebral lesion is confined to the left hemisphere, the right, intact hemisphere may afford compensation in the tactile recognition of stimuli, although a disconnection between right somatosensory associative areas and language areas in the left hemisphere induces unilateral, left-side tactile aphasia (Degos, Gray, Louarn, Ansquer, Poirier, & Barbizet, 1987; Dimond, Scammell, Brouwers, & Weeks, 1977; Gersh & Damasio, 1981; Kawamura, Hirayama, & Yamamoto, 1989). When bilateral, more widespread cerebral damage occurs, the patients may manifest bilateral tactile agnosia (Nakamura et al., 1998). The fuzzy boundary between tactile agnosia and tactile aphasia derives from the close connection between the somatosensory areas and the cortical regions of semantic memory. This functional contiguity is also demonstrated by patients such as the one described by Ohtake, Fujii, Yamadori, Fujimori, Hayakawa, and Suzuki, 2001. This patient presented multimodal agnosia in the visual and tactile modality. His fluctuating performance in recognizing objects was modulated by his verbal ability. In particular, misnamed objects were used and drawn according to the wrong name. Thus, the authors suggest that a dynamic mechanism underlay this associative multimodal agnosia, implying a rivalry between bottom-up and top-down processes. Farah (1990), for example, proposed that stimuli activate visual analysis in a bottom-up fashion, while the spatial attention system and the object-recognition systems have a top-down activation role. This kind of model allows interaction between opposite-flow cognitive processes. According to the site of cerebral lesion, rivalry between central and peripheral mechanisms may occur. In the case of the patient described by Ohtake, the semantic system was strongly activated when verbalization occurred, generating a mental

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image that competed with the perceptual information monitored by the right hemisphere (Ohtake et al., 2001). The literature does not always provide convergent data on the implication of spatial factors in tactile agnosia. In a large group of brain-damaged patients, Semmes (1965) found that those affected by tactile agnosia were also impaired in some spatial tasks, in the absence of elementary sensory defects. Thus, she proposed that this deficit is secondary to a more general spatial deficit. On the other hand, more recently, Reed, Caselli, and Farah (1996) described a single patient with tactile agnosia, without significant general spatial impairment, while performing the same tests used in Semmes’ 1965 study. Delay (1935) was the first to point out the problem involved in distinguishing between elementary deficits and hyloagnosis and morphoagnosis. He observed cases of disproportion between severe morphoagnosis and too mild impairment of basic spatial analysers. He suggested that defective shape recognition has to be ascribed to a higher-level spatial integration (Delay, 1935). Our impression, however, is that there are too many different spatial factors involving personal and extrapersonal space. In the studies attempting to find a relationship between tactile agnosia and supramodal spatial deficits, some of the tasks employed involve extrapersonal space, while object recognition is much more a spatial task interacting with personal coordinates. Thus, the finding of a more general spatial disturbance associated with tactile agnosia is not excluded as a casual association but instead is considered the consequence of a common, complex cognitive dysfunction. However, studies adopting more specific tests, such as identifying the shape of a wooden block by running the finger of the ipsilesional hand along its raised sides, have revealed a significantly more defective performance in right-brain-damaged patients (De Renzi & Scotti, 1969). This finding suggests the influence of a spatial factor in morphoagnosis. Saetti, De Renzi, and Comper (1999) provided further support of this hypothesis. They describe a single patient with amorphoagnosis associated with the inability to recognize tactually the right orientation of lines. The contrasting data in the literature derive from the existence of two mechanisms underlying tactile agnosia: the first, which appears only in the contralateral hand, is related to parietal lesions and induces a defect of the high-level processing of somatosensory information, culminating in the structured description of the object; the second may involve a profound derangement of spatial skills, such as line orientation (as the single case described by Saetti et al., 1999), in turn causing bilateral morphoagnosis. We suggest that if this is true, it is restricted only to the apperceptive level of tactile recognition. Furthermore, this theory left the problem of a right- or left-hemispheric specialization, whatever the level of derangement, still unsolved.

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Hemispheric competence in tactile object recognition at the apperceptive and the associative levels: evidence from braindamaged patients Right-hemisphere specialization for the apperceptive level and lefthemisphere specialization for the associative level have been proven in both visual and auditory modalities (Vignolo, 1969, 1972). Interesting observations were also made on epileptic patients who had undergone surgical treatment. In particular, cerebral commissurotomy offers a unique opportunity to study the two hemispheres in relative isolation. Milner and Taylor (1972) studied a group of patients with section of the interhemispheric commissures, while performing sensory elementary tasks (pressure sensitivity, two-point discrimination, and finger-position sense) and two matching to sample tasks, the former including stimuli chosen expressly for their non-verbal character (wire figures), and the latter with common objects. Subjects were asked to identify, among distractors, the stimulus presented before the recognition task. The authors found that there was superiority of left-hand performance over the right hand on the meaningless test. These results demonstrate that the recognition of shapes without meaning does not require the intervention of verbal coding, in order to retain the mnestic trace and that the right hemisphere has a specific role in processing the spatial relations of complex stimuli. In accordance with this observation, Bottini, Cappa, and Vignolo (1991) found the same anatomical specialization in the tactile domain, through a somaesthetic-visual matching task. The authors studied 49 right-handed patients, 20 with a single right-brain lesion and 29 with a single left-brain lesion. Only right-brain-damaged patients showed impairment in the meaningless object-recognition test (apperceptive agnosia), while right-braindamaged patients were impaired on the meaningful object-recognition test (associative agnosia). This functional dichotomy has been confirmed as a strong double dissociation. In addition, patients with auditory comprehension impairment (investigated by the Token Test) showed a significant correlation between the degree of linguistic deficit and performance in the associative task. These results suggest that cognitive impairment in these patients is more conceptual than purely perceptual in nature. The same dissociation was confirmed in a purely (intramodal) somaesthetic task (Bottini, Cappa, Sterzi, & Vignolo, 1995). Forty right- and left-hemispheric brain-damaged patients and 10 normal controls were studied with two intramodal somaesthetic matching tasks. The authors found a double dissociation between site of hemispheric lesion (right and left) and level of recognition impairment (apperceptive and associative): the right-hemispheric lesion impaired the apperceptive, but not the associative task, while, conversely, the left-hemispheric lesion impaired the associative, but not the apperceptive task. The existence of such a dissociation supports the idea that the cognitive model of object recognition does not imply a sequential structure (Figure 16.2). In the case of familiar stimuli, very early

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Figure 16.2 Apperceptive and associative levels of object recognition in a serial or in a parallel model. hms: hemisphere.

sensory processing may directly contact the left hemisphere, which is responsible for meaningful object recognition. When subjects are asked to identify tactually and recognize, among distractors, meaningless, and thus unfamiliar, objects inducing a high perceptual degree of difficulty, the perceptive resources of the right hemisphere are required. Other authors have proposed the same hypothesis in the visual domain (Humphreys, Riddoch, & Quinlan, 1988; McCarty & Warrington, 1990).

Summary In conclusion, comprehending the somatosensory function requires deep investigation of different levels of cognitive processing, including elementary functions such as touch and proprioception, which are equally involved in object-exploration tasks. Furthermore, manipulating stimuli induces interaction between the somatosensory cortices and the premotor areas. Higher cognitive processes are required to accomplish object recognition and build up a complete object representation. This complex interconnection between somatosensory, premotor, and associative (mainly linguistic) cerebral areas justifies the effort to identify and separate the numerous functional components involved, by means of adequate and sufficiently specific tasks in normal subjects. An even greater challenge is presented by the differential diagnosis of tactile object exploration/identification and recognition in braindamaged patients, considering that the different, currently available cognitive models have not yet allowed us to clarify the TOR mechanisms.

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References Bauer, R. M. (1993). Agnosia. In K. M. Heilman & E. Valenstein (Eds.), Clinical neuropsychology (pp. 215–278). New York: Oxford University Press. Bay, E. (1944). Zum Problem der taktilen Agnosie. Deutsche Zeitschrift für Nervenheilkunde, 156, 64–96. Beauvois, M. F., Saillant, B., Meininger, V., & Lhermitte, F. (1978). Bilateral tactile aphasia: A tacto-verbal dysfunction. Brain, 101, 381–401. Binkofski, F., Buccino, G., Stephan, K. M., Rizzolatti, G., Seitz, R. J., & Freund, H. J. (1999). A parieto-premotor network for object manipulation: Evidence from neuroimaging. Experimental Brain Research, 128, 210–213. Bottini, G., Cappa, S. F., Sterzi, R., & Vignolo, L. A. (1995). Intramodal somaesthetic recognition disorders following right and left hemisphere damage. Brain, 118, 395–399. Bottini, G., Cappa, S. F., & Vignolo, L. A. (1991). Somesthetic-visual matching disorders in right and left hemisphere-damaged patients. Cortex, 27, 223–228. Brodmann, K. (1909). Vergleichende Lokalisationslehre der Grosshirnrinde. Leipzig: Barth. Burton, H. (1986). Second somatosensory cortex and related areas. In E. G. Jones & A. Peters (Eds.), Cerebral cortex. Vol. 5: Sensory-motor areas and aspects of cortical connectivity (pp. 31–98). New York: Plenum. Burton, H., Videen, T. O., & Raichle, M. E. (1993). Tactile-vibration-activated foci in insular and parietal-opercular cortex studied with positron emission tomography: Mapping the second somatosensory area in humans. Somatosensory and Motor Research, 10, 297–308. Caselli, R. J. (1991). Rediscovering tactile agnosia. Mayo Clinical Procedures, 66, 129–142. Coghill, R. C., Talbot, J. D., Evans, A. C., Meyer, E., Gjedde, A., Bushnell, M. C., et al. (1994). Distributed processing of pain and vibration by the human brain. Journal of Neuroscience, 14, 4095–4108. Colebatch, J. G., Deiber, M. P., Passingham, R. E., Friston, K. J., & Frackowiak, R. S. (1991). Regional cerebral blood flow during voluntary arm and hand movements in human subjects. Journal of Neurophysiology, 65, 1392–1401. Corkin, S., Milner, B., & Rasmussen, T. (1970). Somatosensory thresholds—contrasting effects of postcentral-gyrus and posterior parietal-lobe excisions. Archives of Neurology, 23, 41–58. Damasio, A. R. (1989). Time-locked multiregional coactivation: A systems-level proposal for the neural substrates of recall and recognition. Cognition, 33, 25–62. Degos, J. D., Gray, F., Louarn, F., Ansquer, J. C., Poirier, J., & Barbizet, J. (1987). Posterior callosal infarction. Clinicopathological correlations. Brain, 110, 1155–1171. Delay, J. P. L. (1935). Les Astéréognosies. Pathologie du toucher. Clinique, physiologie, topographie. Paris: Masson. De Renzi, E., & Scotti, G. (1969). The influence of spatial disorders in impairing tactual discrimination of shapes. Cortex, 5, 53–62. Dimond, S. J., Scammell, R. E., Brouwers, E. Y., & Weeks, R. (1977). Functions of the centre section (trunk) of the corpus callosum in man. Brain, 100, 543–562. Disbrow, E., Roberts, T., & Krubitzer, L. (2000). Somatotopic organization of cortical fields in the lateral sulcus of Homo sapiens: Evidence for SII and PV. Journal of Comparative Neurology, 418, 1–21.

16. Somaesthetic recognition disorders

301

Endo, K., Miyasaka, M., Makishita, H., Yanagisawa, N., & Sugishita, M. (1992). Tactile agnosia and tactile aphasia: Symptomatological and anatomical differences. Cortex, 28, 445–469. Farah, M. J. (1990). Visual agnosia. Cambridge, MA: MIT Press. Fox, P. T., Burton, H., & Raichle, M. E. (1987). Mapping human somatosensory cortex with positron emission tomography. Journal of Neurosurgery, 67, 34–43. Friedman, D. P., & Murray, E. A. (1986). Thalamic connectivity of the second somatosensory area and neighboring somatosensory fields of the lateral sulcus of the macaque. Journal of Comparative Neurology, 252, 348–373. Gelnar, P. A., Krauss, B. R., Szeverenyi, N. M., & Apkarian, A. V. (1998). Fingertip representation in the human somatosensory cortex: An fMRI study. NeuroImage, 7, 261–283. Gersh, F., & Damasio, A. R. (1981). Praxis and writing of the left hand may be served by different callosal pathways. Archives of Neurology, 38, 634–636. Grafton, S. T., Woods, R. P., & Mazziotta, J. C. (1993). Within-arm somatotopy in human motor areas determined by positron emission tomography imaging of cerebral blood flow. Experimental Brain Research, 95, 172–176. Head, H. (1918). Sensation and the cerebral cortex. Brain, 41, 57–253. Head, H., & Holmes, G. (1911). Sensory disturbance from cerebral lesions. Brain, 34, 102–254. Hécaen, H., & Albert, M. L. (1978). Human neuropsychology. New York: Wiley. Humphreys, G. W., Riddoch, M. J., & Quinlan, P. T. (1988). Cascade processes in picture identification. Cognitive Neuropsychology, 5, 67–104. Hyvarinen, J. (1982). Posterior parietal lobe of the primate brain. Physiological Review, 62, 1060–1129. Ingvar, D. H. (1975). Patterns of brain activity revealed by measurements of regional cerebral blood flow. In D. H. Ingvar & N. A. Lassen (Eds.), Brain work (pp. 397–413). Copenhagen: Munksgaard. Jancke, L., Kleinschmidt, A., Mirzazade, S., Shah, N. J., & Freund, H. J. (2001). The role of the inferior parietal cortex in linking the tactile perception and manual construction of object shapes. Cerebral Cortex, 11, 114–121. Kaas, J. H. (1983). What, if anything, is SI? Organization of first somatosensory area of cortex. Physiological Review, 63, 206–231. Kaas, J. H. (1990). Somatosensory system. In G. Paxinos (Ed.), The human nervous system (pp. 813–844). San Diego, CA: Academic Press. Kaas, J. H., Nelson, R. J., Sur, M., Lin, C. S., & Merzenich, M. M. (1979). Multiple representations of the body within the primary somatosensory cortex of primates. Science, 204, 521–523. Kawamura, M., Hirayama, K., & Yamamoto, H. (1989). Different interhemispheric transfer of kanji and kana writing evidenced by a case with left unilateral agraphia without apraxia. Brain, 112, 1011–1018. Lissauer, E. (1890). Ein Fall von Seelenblindheit nebst einem Beitrag zur Theorie derselben. Archiv Psychiatrie und Nervenkrankheiten, 21, 222–270. Luders, H., Lesser, R. P., Dinner, D. S., Hahn, J. F., Salanga, V. & Morris, H. H. (1985). The second sensory area in humans: Evoked potential and electrical stimulation studies. Annals of Neurology, 17, 177–184. McCarty, R. A., & Warrington, E. K. (1990). Cognitive neuropsychology. A clinical introduction. San Diego, CA: Academic Press. Merzenich, M. M., Kaas, J. H., Sur, M., & Lin, C. S. (1978). Double representation of

302

Bottini and Gandola

the body surface within cytoarchitectonic areas 3b and 1 in “SI” in the owl monkey (Aotus trivirgatus). Journal of Comparative Neurology, 181, 41–73. Mesulam, M. M., & Mufson, E. J. (1982). Insula of the old world monkey. I. Architectonics in the insulo-orbito-temporal component of the paralimbic brain. Journal of Comparative Neurology, 212, 1–22. Mesulam, M. M., & Mufson, E. J. (1986). The insula of Reil in man and monkey. Architectonics connectivity and function. In E. G. Jones & A. Peters (Eds.), Cerebral cortex. Vol. 4: Association and auditory cortices (pp. 179–226). New York: Plenum. Milner, B., & Taylor, L. (1972). Right-hemisphere superiority in tactile patternrecognition after cerebral commissurotomy: Evidence for nonverbal memory. Neuropsychologia, 10, 1–15. Moore, C. I., Gehi, A., Guimereas, A. R., Corkin, S., Rosen, B. R., & Stern, C. E. (1966). Somatotopic mapping of cortical areas SI and SII using fMRI. NeuroImage, 6, S333. Mufson, E. J., Mesulam, M. M., & Pandya, D. N. (1981). Insular interconnections with the amygdala in the rhesus monkey. Neuroscience, 6, 1231–1248. Nakamura, J., Endo, K., Sumida, T., & Hasegawa, T. (1998). Bilateral tactile agnosia: A case report. Cortex, 34, 375–388. Ohtake, H., Fujii, T., Yamadori, A., Fujimori, M., Hayakawa, Y., & Suzuki, K. (2001). The influence of misnaming on object recognition: A case of multimodal agnosia. Cortex, 37, 175–186. Pardo, J. V., Fox, P. T., & Raichle, M. E. (1991). Localization of a human system for sustained attention by positron emission tomography. Nature, 349, 61–64. Paulesu, E., Frackowiak, R. S., & Bottini, G. (1997). Maps of somatosensory systems. In R. S. Frackowiak (Ed.), Human brain function (pp. 183–242). San Diego, CA: Academic Press. Penfield, W. J. & Jasper, H. (1954). Epilepsy and the functional anatomy of the human brain. Boston: Little Brown. Penfield, W. J. & Rasmussen, T. (1950). The cerebral cortex of man. New York: Macmillan. Platz, T. (1996). Tactile agnosia. Casuistic evidence and theoretical remarks on modality-specific meaning representations and sensorimotor integration. Brain, 119, 1565–1574. Poggio, G. F., & Mountcastle, V. B. (1963). The functional properties of ventrobasal thalamic neurons studied in unanesthetized monkeys. Journal of Neurophysiology, 26, 775–806. Rao, S. M., Binder, J. R., Hammeke, T. A., Bandettini, P. A., Bobholz, J. A., Frost, J. A., et al. (1995). Somatotopic mapping of the human primary motor cortex with functional magnetic resonance imaging. Neurology, 45, 919–924. Reed, C. L., Caselli, R. J., & Farah, M. J. (1996). Tactile agnosia. Underlying impairment and implications for normal tactile object recognition. Brain, 119, 875–888. Reed, C. L., Shoham, S., & Halgren, E. (2004). Neural substrates of tactile object recognition: An fMRI study. Human Brain Mapping, 21, 236–246. Remy, P., Zilbovicius, M., Leroy-Willig, A., Syrota, A., & Samson, Y. (1994). Movement- and task-related activations of motor cortical areas: A positron emission tomographic study. Annals of Neurology, 36, 19–26. Robinson, C. J. & Burton, H. (1980a). Somatic submodality distribution within the second somatosensory (SII), 7b, retroinsular, postauditory, and granular insular cortical areas of M. fascicularis. Journal of Comparative Neurology, 192, 93–108.

16. Somaesthetic recognition disorders

303

Robinson, C. J., & Burton, H. (1980b). Somatotopographic organization in the second somatosensory area of M. fascicularis. Journal of Comparative Neurology, 192, 43–67. Roland, E., & Larsen, B. (1976). Focal increase of cerebral blood flow during stereognostic testing in man. Archives of Neurology, 33, 551–558. Roland, P. E. (1987). Somatosensory detection in patients with circumscribed lesions of the brain. Experimental Brain Research, 66, 303–317. Ruben, J., Schwiemann, J., Deuchert, M., Meyer, R., Krause, T., Curio, G., et al. (2001). Somatotopic organization of human secondary somatosensory cortex. Cerebral Cortex, 11, 463–473. Rudge, P., & Warrington, E. K. (1991). Selective impairment of memory and visual perception in splenial tumours. Brain, 114, 349–360. Saetti, M. C., De Renzi, E., & Comper, M. (1999). Tactile morphagnosia secondary to spatial deficits. Neuropsychologia, 37, 1087–1100. Seitz, R. J. & Roland, P. E. (1992). Vibratory stimulation increases and decreases the regional cerebral blood flow and oxidative metabolism: A positron emission tomography (PET) study. Acta Neurologica Scandinavica, 86, 60–67. Semmes, J. (1965). A non-tactual factor in astereognosis. Neuropsychologia, 3, 295–314. Sterzi, R., Bottini, G., Celani, M. G., Righetti, E., Lamassa, M., Ricci, S., et al. (1993). Hemianopia, hemianaesthesia, and hemiplegia after right and left hemisphere damage. A hemispheric difference. Journal of Neurology, Neurosurgery, and Psychiatry, 56, 308–310. Vallar, G., Bottini, G., Rusconi, M. L., & Sterzi, R. (1993). Exploring somatosensory hemineglect by vestibular stimulation. Brain, 116, 71–86. Vallar, G., Sterzi, R., Bottini, G., Cappa, S., & Rusconi, M. L. (1990). Temporary remission of left hemianesthesia after vestibular stimulation. A sensory neglect phenomenon. Cortex, 26, 123–131. Vignolo, L. A. (1969). Auditory agnosia: A review and report of recent evidence. In A. L. Benton (Ed.), Contributions to clinical neuropsychology. Chicago: Aldine. Vignolo, L. A. (1972). Les Deux Niveaux de l’agnosie. In H. Hécaen (Ed.), Neuropsychologie de la perception visuelle (pp. 222–240). Paris: Masson. Vogt, C., & Vogt, O. (1919). Allgemeinere Ergebnisse unserer Hirnforschung. Journal of Psychology and Neurology, 25, 279–462. von Frey, M. (1895). Beiträge zur Sinnesphysiologie der Haut, Dritte Mittheilung. Berichte über die Verhandlungen der Königlich Sächsischen Gesellschaft der Wissenschaften zu Leipzig, 47, 166–184. Warrington, E. K. & Taylor, A. M. (1978). Two categorical stages of object recognition. Perception, 7, 695–705. Wernicke, K. (1895). Zwei Fälle von Rindenläsion. Arbeiten aus der psychiatrischen Klinik in Breslau, 2, 35–52.

SECTION V

Neglect, attentional, and executive disorders

17 Subcortical neglect Giuseppe Vallar

Some episodic recollections In the late 1970s, the Centro di Neuropsicologia of the Neurological Clinic of the State University of Milan enjoyed a very productive phase. The leading scientist of the so-called Milan Group (Grossi & Boller, 1996), Ennio De Renzi, had moved to the Neurological Clinic of the University of Modena. But research in Milan was still very active. Since the beginning in the late 1950s, the main focus of interest had changed. Hemispheric asymmetry was now a less central issue (De Renzi, 1967, 2001). Topics such as the rehabilitation of aphasia (Basso, Capitani, & Vignolo, 1979); the anatomical correlates of aphasic disorders in left-brain-damaged patients, as assessed by the novel neuroradiological technique of the CT scan, which allowed mapping of the lesion site on standard templates of the brain (Mazzocchi & Vignolo, 1979); and, with respect to the right hemisphere, unilateral spatial neglect (Bisiach & Luzzatti, 1978; Marshall & Halligan, 2003) were being actively investigated. A few years later, the Milan Group and the Centro di Neuropsicologia broke up, Luigi Vignolo moving to the Neurological Clinic of the University of Brescia (1982), Hans Spinnler to the First Neurological Clinic of the University of Milan in the San Paolo Hospital (1983), and Edoardo Bisiach to the Department of Psychology of the University of Padua (1990). During those years, I was attending the speciality class in neurology in the Neurological Clinic (the Padiglione Ponti) of the Policlinico di Milano (Galimberti & Rebora, 2005), assigned to the female ward (Sala Biffi), under the tutorship of Edoardo Bisiach. Luigi Vignolo had the responsibility of one male ward, in the Sala Verga.1 Accordingly, I did not have the opportunity of learning the practice of neurology, including neurological examination, from Vignolo, but I attended some of his lessons. On at least two occasions, I was deeply impressed by the clarity and thoroughness of his teaching, coupled with an understated attitude. His complete treatment of the neurology of the ocular muscles (Cogan, 1956) gave me a definite overview of this complex part of the neurological examination. In the Thursday afternoon seminars of Speciality Class, Vignolo’s lesson on the classical taxonomy of aphasia was an illuminating account of the Wernicke–Lichtheim model

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and its diagnostic, clinical value (Vignolo, 1977), which remained largely unchanged during the days of cognitive neuropsychology (Vallar, 2000). In the late 1970s and early 1980s, Vignolo was also investigating the aphasic disorders caused by damage to subcortical structures, such as the thalamus and the basal ganglia, and, by implication, the role of these nuclei in language processing (see Chapter 8, this volume), using the then novel technique of the CT scan (Mazzocchi & Vignolo, 1978). This non-invasive neuroimaging method allowed anatomoclinical correlation studies in large series of braindamaged patients, providing, for the first time, an explicit and direct in vivo image of the brain and its lesions (Oldendorf, 1978). In that time, under the guidance of Edoardo Bisiach, I was approaching the syndrome of unilateral spatial neglect, which was revealing its manifold, multicomponent nature (e.g. Bisiach et al., 1983), as were other disorders, such as dyslexia (Coltheart, Patterson, & Marshall, 1980; Patterson, Marshall, & Coltheart, 1985). Bisiach was mainly concerned with the representational aspects of spatial neglect (see the Festschrift for Edoardo Bisiach: Marshall & Vallar, 2004). Prompted also by Vignolo’s work on the neuroanatomical correlates of aphasia, using the CT scan, I developed an interest in the neuroanatomical correlates of neglect (Bisiach et al., 1984; Vallar & Perani, 1986). I was also led to this enterprise by the feeling that this research field was underdeveloped. Systematic studies in large series of brain-damaged patients—coupling adequate localization of the lesion with appropriate diagnostic assessment—were lacking, with a few exceptions not specifically concerned with neglect (Kertesz & Dobrowolsky, 1981). The available evidence was based on a few case reports (Hécaen et al., 1956; Heilman & Valenstein, 1972a), corroborating the traditional posterior parietal correlate (Botez, Botez, & Oliver, 1985; Critchley, 1953; Jewesbury, 1969), but also suggesting a role for other cortical lesion sites, such as the frontal lobe (Heilman & Valenstein, 1972b) and the cingulate cortex (Watson et al., 1973). At present, there is a novel rise of interest in the neural correlates of spatial neglect (Berti et al., 2005; Doricchi & Tomaiuolo, 2003; Karnath, Baier, & Nagele, 2005a; Karnath, Ferber, & Himmelbach, 2001; Mort et al., 2003), after a period when research in humans focused more on the functional aspects of the syndrome (see Karnath, Milner, & Vallar, 2002, for review). My own anatomoclinical correlation studies in the mid-1980s included the observation that spatial neglect, as in aphasia, could be associated with vascular lesions confined to subcortical structures and sparing the cortex (Vallar, 1993; Vallar & Perani, 1987). My interest in the role of the subcortical grey nuclei and the white matter was not confined to spatial neglect but extended to the frontal lobe syndrome (Sterzi & Vallar, 1978), and aphasia. Work on aphasia resulted in one paper with Vignolo and two of his students, Stefano Cappa and Costanza Papagno (Cappa et al., 1986), and in applying the then novel neuroimaging techniques of single-photon emission tomography (SPET) and positron emission tomography (PET) to the investigation of cortical function in patients with unilateral subcortical stroke, showing and not showing aphasia or neglect (Perani et al., 1987, 1993; Vallar et al., 1988).

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The research performed in the 1980s on the neuropsychological disorders associated with subcortical lesions was discussed in an international conference held in Como, Italy, in September 1989. The papers presented there, many main investigators of the relationship between subcortical structures and cognition taking part, were published in a book I co-edited with Stefano Cappa and C.-W. Wallesch (1992), who also had an interest in the role of the subcortical grey nuclei in language and aphasia (Wallesch, 1985; Wallesch et al., 1983).

1970: “subcortical” neglect A few instances of neglect phenomena in patients with subcortical lesions may be found in the classic literature (Pick, 1898, pp. 168–185). It was in the 1970s, however, that both animal and human research provided extensive evidence that unilateral subcortical damage may cause neglect contralateral to the side of the lesion (contralesional). Lesions of the nigrostriatal system, the thalamus, and the superior colliculus all result in deficits in orienting and responding to contralesional visual and somatosensory (in some studies, auditory and olfactory) stimuli. These orienting impairments cannot be traced to sensory deficits, and they reflect a higher-order disorder (reviewed in Milner, 1987). In man, it was in the 1970s, with the introduction of the non-invasive CT scan technique in neuroradiological practice (reviewed in Perani & Cappa, 1999), that a definite association between subcortical damage and left unilateral spatial neglect was established. As “cortical” neglect, neglect associated with subcortical lesions shows a hemispheric asymmetry: contralesional neglect is more frequent and severe after damage to the right cerebral hemisphere. Neglect represents, in this respect, the right-sided counterpart of “subcortical aphasia” (see Chapter 8, this volume), which is typically associated with left-hemispheric damage (the issue of these hemispheric asymmetries is not further considered here; see the review in Cappa & Vallar, 1992). There are reports of right-sided neglect associated with left subcortical damage, but this association is typically less frequent and the deficit less severe, in accord with the pattern of “cortical” neglect in left-brain-damaged patients (Ringman et al., 2004). Spatial neglect may be associated with ischaemic or haemorrhagic lesions involving the thalamus (Cambier, Elghozi, & Strube, 1980; Oxbury, Campbell, & Oxbury, 1974; Schott et al., 1981; Watson & Heilman, 1979; Watson, Valenstein, & Heilman, 1981), the basal ganglia (Damasio, Damasio, & Chang Chui, 1980; Ferro, Kertesz, & Black, 1987; Healton et al., 1982; Hier et al., 1977), and the white matter, particularly the posterior limb of the internal capsule (Cambier et al., 1983; Ferro & Kertesz, 1984; Masson et al., 1983; Vallar et al., 1990, patient no. 2), but also the corona radiata (Stein & Volpe, 1983; Vallar & Perani, 1986). While lesions confined to the subcortical white matter are only rarely associated with neglect (Vallar & Perani, 1986), in patients with cortico-subcortical lesions, the white-matter fibre bundles

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connecting the posterior and anterior regions of the brain are frequently damaged, namely the inferior (Leibovitch et al., 1998) and, particularly, the superior longitudinal fasciculus, which provides parietofrontal connections (Doricchi & Tomaiuolo, 2003; Leibovitch et al., 1998).

Cortico-subcortical networks The observation that lesions confined to subcortical grey nuclei, such as the thalamus and the basal ganglia, may bring about aphasia or neglect is prima facie inconsistent with the time-honoured view that the cerebral cortex is the sole neural substrate of cognition (Gall & Spurzheim, 1810; Lichtheim, 1885; Wernicke, 1874/1966–8). Lesions confined to white-matter fibre tracts, by contrast, are compatible with the classic anatomoclinical models of the so-called diagram-makers (Lichtheim, 1885; Morton, 1984; Wernicke, 1874/ 1966–8): the neuropsychological deficits are brought about by a disconnection between cortical areas, which are made unable to receive and send appropriate inputs (Catani & ffytche, 2005; Geschwind, 1965a, 1965b). Soon after the observations, summarized earlier, of an association between subcortical lesions and cognitive disorders, such as aphasia and neglect, a number of studies investigated the functional anatomy of the cerebral cortex in patients with subcortical lesions. SPET and PET revealed a cortical dysfunction (hypoperfusion and hypometabolism) in patients with aphasia and neglect associated with subcortical lesions (Baron et al., 1986; see also Colson et al., 2001, for EEG-based evidence suggesting cortical dysfunction; Hillis et al., 2000, 2002, 2003; Perani et al., 1987; Weiller et al., 1990, 1993). More recent investigations using diffusion and perfusion MRI in patients with subcortical lesions (subcortical white-matter and grey-matter structures) and neglect have also shown cortical hypoperfusion (Hillis et al., 2002; 2005; Karnath et al., 2005b). The role of cortical dysfunction is also supported by the finding that recovery from neglect parallels the reduction of the cortical hypoperfusion or hypometabolism (Hillis et al., 2002; Perani et al., 1993; Vallar et al., 1988). Taken together, these results suggest that dysfunction at the cortical level, as indexed by hypoperfusion and hypometabolism, may be a relevant factor in unilateral spatial neglect in patients with subcortical lesions. These conclusions are largely compatible with the traditional assignment of a main role to the cerebral cortex in cognitive function. Possible mechanisms involved in producing this cortical dysfunction far removed from the subcortical lesion, include the following: small (and undetected) cortical lesions; mass effects due to compression by the primary subcortical lesion, either direct or of vascular supply; in the case of arterial occlusion, reduced blood flow in areas adjacent to the infarction, sufficient for viability but not adequate for normal function (ischaemic penumbra); and partially incomplete neuronal loss due to reduced blood flow (incomplete infarction). While all these factors may undoubtedly play a role, patients with subcortical lesions and cognitive

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deficits have been described in whom additional cortical lesions were not found at post-mortem examination, the ischaemic lesion was small and well demarcated with mass effects being unlikely, and no detectable arterial occlusion was detected (see review and references in Cappa & Vallar, 1992). Another relevant factor is the reduced functional activity of cortical regions, due to deprivation of afferent inputs from the damaged subcortical structures (Feeney & Baron, 1986; see Reggia, 2004, for a computational model; Witte & Stoll, 1997). This is a revision and a development of the concept of remote effects (diaschisis), originally proposed by von Monakow (Finger, Koehler, & Jagella, 2004; von Monakow, 1914). The diaschisis interpretation of remote effects is based on the existence of neural connections that provide activation of specific regions of the brain. This point is illustrated by research in animals showing that cortical (e.g. Carmichael et al., 2004) and subcortical (Girault et al., 1985; London et al., 1984) lesions produce remote effects in connected regions that receive major afferent projections. Within the framework of cortico-subcortical networks discussed earlier, attempts were made to elucidate whether particular subcortical lesion sites are more frequently associated with the syndrome of unilateral spatial neglect. Traditionally, the closest association of unilateral spatial neglect is with lesions involving the posterior parietal cortex (supramarginal gyrus) at the temporoparietal junction (Hécaen et al., 1956; Heilman & Valenstein, 1972a; Vallar & Perani, 1986), and a role for other close regions, such as the superior temporal (Karnath et al., 2001), and the angular gyri (Mort et al., 2003), has been recently suggested. Studies in large series of brain-damaged patients have shown that the association of spatial neglect with subcortical damage is less close than with lesions involving the cortex. In a series of 59 patients with cortico-subcortical lesions (Vallar & Perani, 1987), assessed within 1 month after stroke onset, 34 patients (58%) showed neglect on a circle cancellation task. When the patients with posterior or extensive anteroposterior lesions were considered, the number of patients showing neglect increased to 33 out of 47 (70%). In the same series, 13 out of 51 patients with subcortical lesions (25%) exhibited left neglect; of these 13 patients, 12 (92%) had lesions involving the thalamus, the basal ganglia, or both structures. In an acute cohort of stroke patients, the frequency of neglect, assessed by scene description (the Cookie Theft Picture) and tactile double simultaneous stimulation, was 56% (63/113) in right-brain-damaged patients with cortico-subcortical lesions (not involving the thalamus or the basal ganglia), and 27% (20/75) in right-braindamaged patients with damage confined to the basal ganglia/internal capsule or the thalamus (the corona radiata may have been involved in both the “cortical” and the “subcortical” groups of this study). At 3-month follow-up, left neglect was found in 20% of right-brain-damaged patients with cortical lesions (20/102) and in 1 out of 71 patients with subcortical damage (Ringman et al., 2004, Table 2). Evidence for a specific role of the subcortical grey nuclei is also provided by patients who undergo functional neurosurgery for the relief of Parkinson’s disease. Thalamotomy may bring about

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contralesional neglect (Perani, Nardocci, & Broggi, 1982; Velasco et al., 1986; Vilkki, 1984). Finally, the view that the subcortical grey nuclei participate in specific cortico-subcortical circuits involved in spatial cognition is supported by investigations in brain-damaged patients with focal thalamic infarctions. Spatial disorders, of which neglect is a main component, are more frequently associated with focal lesions in the vascular territories of the tuberothalamic (reticular, anterior, ventral-anterior, and rostral ventral-lateral nuclei, ventral pole of the medial dorsal nucleus), and paramedian (principally, the intralaminar and medial dorsal nuclei, the ventromedial pulvinar) arteries (Bogousslavsky, Regli, & Uske, 1988b; Schmahmann, 2003). In conclusion, data from individual patient studies and series of brain-damaged patients suggest a main role of posterior and medial thalamic damage, as compared with more anterior lesions (Karnath, Himmelbach, & Rorden, 2002; see Vallar, 1993, for a review). To summarize, anatomoclinical correlation studies performed in braindamaged patients suggest that subcortical structures, particularly the basal ganglia and the thalamus, are component parts of cortico-subcortical circuits concerned with spatial attention and representation. Functional imaging studies using SPET and PET have repeatedly revealed the concomitant presence of cortical hypoperfusion and hypometabolism, suggesting that the effects of subcortical damage should be interpreted in terms of a disruption of cortico-subcortical networks brought about by the subcortical lesion. On the basis of anatomoclinical correlation studies performed in large series of brain-damaged patients, the conclusion can be drawn that, while the observation that lesions restricted to subcortical structures may cause contralesional neglect is confirmed, the cortical regions of the network involved in spatial attention and representation are likely to play a major, though not exclusive, role. While it is unlikely that the disruptive effects of subcortical lesions on spatial cognition may be accounted for solely in terms of a remote cortical dysfunction, the relevance of cortical activity, hypothesized by the classic neurofunctional models of cognition of the nineteenth century (Lichtheim, 1885; Wernicke, 1874/1966–8), is basically confirmed. This, in turn, may reflect the major neuronal mass available for computations in the cortex as compared with that provided by subcortical structures. At the anatomoclinical level, this is indexed by the observation, confirmed many times, that there is a direct relationship between the size of the lesion and the frequency of neglect (Kertesz & Dobrowolsky, 1981; Leibovitch et al., 1998; Ringman et al., 2004; Vallar & Perani, 1986). Figure 17.1 shows the cortical regions of the right cerebral hemisphere whose damage is associated with unilateral spatial neglect. Figure 17.2 is a schematic representation of the cortical and subcortical structures involved in spatial representation and attention. In recent years, in the broader context of the currently rising prominence of disconnection syndromes (see Catani & ffytche, 2005, for a recent review; Geschwind, 1965a, 1965b; Lichtheim, 1885; Wernicke, 1874/1966–8),

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the suggestion has been made, from studies both in the monkey (Gaffan & Hornak, 1997) and in neurological patients, that damage (Bird et al., 2006; Doricchi & Tomaiuolo, 2003) or temporary inactivation (Thiebaut de Schotten et al., 2005) of white-matter fibre tracts plays a crucial role in bringing about unilateral spatial neglect. These sites include long-range parietofrontal connections (Doricchi & Tomaiuolo, 2003; Thiebaut de Schotten et al., 2005) and the white matter of the occipital lobe, possibly disrupting a tract connecting the parahippocampal and the angular gyri (Bird et al., 2006; Mort et al., 2003). These recent findings are in line with the time-honoured view (see Catani & ffytche, 2005, for a recent reappraisal; Lichtheim, 1885; Wernicke, 1874/1966–8) that damage to both cortical areas and to their long, interterritorial connecting fibres may bring about unilateral spatial neglect, as well as aphasia, agnosia, or apraxia. At present, the finding that these neuropsychological disorders may be associated with damage involving both cortical and subcortical (white matter, grey nuclei) structures supports an approach in which the neural correlates of these functions include both cortical and subcortical structures, as well as their connections (e.g. Figure 17.2) (Cappa & Vallar, 1992; Mesulam, 2002). In this perspective, a focal lesion, be it cortical, subcortical, or both, may interfere with the operation of a broader network, through the mechanisms of remote effects (Feeney & Baron, 1986; Witte & Stoll, 1997). Interestingly, these effects may occur not only after structural lesions, such as a stroke, but also after the dysfunction or “virtual lesion” brought about by repetitive transcranial magnetic stimulation (rTMS). For instance, in the cat, rTMS applied to the posterior and inferior parietal cortex (visual parietal cortex) induces, online (during stimulation), a reduction of 14C-2-deoxyglucose metabolism both in the stimulated cortex and in connected subcortical structures, such as the superior colliculus and the thalamus (the pulvinar, and part of the lateral posterior complex), with no effects in subcortical structures with poor connections with the visual parietal cortex (Valero-Cabré, Payne, & Pascual-Leone, 2007; see also Valero-Cabré et al., 2005).

The cognitive specificity of subcortical neglect The anatomoclinical correlation evidence reviewed in the previous section suggests that subcortical structures such as, first of all, some thalamic nuclei, the basal ganglia, and some white-matter fibre tracts are components of cortico- (premotor frontal and posterior parietal cortices, the temporoparietal junction) subcortical circuits involved in spatial representation and attention (see a recent model in Reep et al., 2004). Accordingly, we can expect that damage to both the cortical and the subcortical components of the network may cause manifestations of the neglect syndrome that are not fundamentally different with respect to the cortical versus subcortical localization of the lesion. Analysis of the neglect-related deficits associated with subcortical lesions should consider, however, that neglect is not conceived any longer as a

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Figure 17.1 Cortical lesion sites associated with neglect. Most anatomoclinical correlation studies show that the lesion responsible for unilateral spatial neglect involves the right inferior parietal lobule (BA 39 and BA 40: red area), particularly the supramarginal gyrus at the temporoparietal junction (black-grey area). Neglect after right frontal damage is less frequent and usually associated with lesions to the frontal premotor cortex, particularly to its more ventral parts (BA 44 and ventral BA 6: blue area). Damage to white-matter fibre bundles that provide connections between the posterior parietal region and the temporoparietal junction, and the frontal premotor cortex, are also relevant (arrow). Neglect may be also associated with damage to the more dorsal and medial regions of the frontal premotor cortex, and to the superior temporal gyrus (azure areas) (modified from Halligan et al., 2003). BA: Brodmann area. (This figure is published in colour at www.psypress.com/brainscans-etc/)

unitary monolithic disorder, encompassing instead (as in aphasia) a number of manifestations that may occur also in isolation. A taxonomy of unilateral spatial neglect is shown in Table 17.1 (Vallar, 1998; Vallar, Bottini, & Paulesu, 2003). Furthermore, even within the most investigated manifestation of neglect (extrapersonal visual neglect), dissociations are present, depending on the particular task used to assess the disorder. Patients may show neglect in line bisection with a rightward directional error, but not in visuomotor exploratory tasks, such as cancellation. The opposite pattern of impairment (defective performance in cancellation tasks with left-sided omissions, but not in line bisection) has been also described (Halligan & Marshall, 1992; Marshall & Halligan, 1995). These observations do not reveal an anatomical counterpart of the behavioural dissociation. Both patient H.D. (defective cancellation/

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Figure 17.2 Cortico-subcortical networks for spatial attention and representation: the premotor frontal areas, the posterior-parietal regions/temporoparietal (TP) junction, the subcortical grey nuclei, and their connections. The main structures whose damage is most frequently associated with neglect in man are in boldface (modified from Mesulam, 2002).

preserved bisection) and patient W.S. (defective bisection/preserved cancellation) had right-sided temporoparietal damage and left visual-field deficits (Halligan & Marshall, 1992). Patient J.B., who was selectively impaired in line bisection but with preserved performance in cancellation tasks, had a posterior subcortical lesion (the posterior limb of the internal capsule and the thalamus) and full visual fields (Marshall & Halligan, 1995; see also a group study in McGlinchey-Berroth et al., 1996). Finally, the search for behavioural differences between patients with cortical and subcortical lesions in the manifestations of the neglect syndrome should also consider that subcortical damage is less frequently associated with neglect than lesions involving the cortex (Ringman et al., 2004; Vallar & Perani, 1986). Of the symptom complex shown in Table 17.1, the main, and more extensively investigated, manifestations of the neglect syndrome shall be considered, namely extrapersonal visual neglect, personal neglect, and anosognosia for hemiplegia. The related disorder of sensory extinction to double simultaneous stimulation (Bisiach & Vallar, 2000; Vallar, 1998), and putative primary neurological impairments (hemianopia, hemianaesthesia, and hemiplegia), in which spatial neglect may play a causal role, exacerbating the disorder (Sterzi et al., 1993; Vallar et al., 1993, 1997), are not reviewed. Defective manifestations of neglect Thalamic damage may bring about all the main defective manifestations of spatial neglect, including extrapersonal visual neglect, assessed by target cancellation (Cappa et al., 1987; Ringman et al., 2004; Vallar & Perani, 1986;

Table 17.1 A taxonomy of the clinical syndrome of unilateral spatial neglect (USN). “Defective” manifestations (the better-known and more extensively investigated aspect of USN) refer to negative phenomena, characterized by the absence of specific behavioural responses, such as impaired exploration of the contralesional side of space or failure to report stimuli presented in that sector of space. “Productive” manifestations refer to positive phenomena, characterized by the presence of specific behaviours A. Defective manifestations Extrapersonal space Dimension Input/output

Personal/bodily space

Variety Perceptual USNa Premotor/intentional USN, directional hypokinesiad Sectors of space Lateral external USNf (with reference to the body) Lateral internal (imaginal) USNf Altitudinalg Reference frames Egocentric USNh Allocentric/object-based USN Sensory modalityi Visual USN(pseudohemianopia) Auditory USN Olfactory USN Processing domainj Facial USN Neglect dyslexia

Hemiasomatognosiab Anosognosiac Motor neglecte

Somatosensory USN

B. Productive manifestations Extrapersonal space

Personal/bodily space

Avoidancek Hyperattention, magnetic attraction towards ipsilesional targets Perseveration and gratuitous productionsm

Somatoparaphrenial

a Defective awareness of targets in the neglected sector of space. b Defective awareness of the contralesional side of the body. c Defective awareness or denial of contralesional motor, somatosensory, and visual half-field deficits. d Defective programming of movements of the ipsilesional limbs toward targets in the neglected, contralesional sector of space. e Failure to move the contralesional limbs, in the absence of primary motor impairment (hemiparesis or hemiplegia). f Along a left-right axis: near, far. g Along a vertical axis: upper, lower. h With reference to the head, the trunk, the limbs. i Defective awareness of sensory input in a particular sensory modality. j Material-specific forms of neglect. k Active withdrawal from contralesional targets. l Delusional beliefs concerning the contralesional side of the body. m Perseveration: the iteration of a behaviour that is no longer appropriate, but continues steadfastly after the termination or change of the task’s demands, or in the absence of the appropriate exciting stimulus. Gratuitous productions: more or less complex behaviours, entirely unnecessary and unrelated to the task’s demands.

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Watson & Heilman, 1979; Watson et al., 1981) or line bisection (Marshall & Halligan, 1995); personal neglect for the contralesional side of the body; anosognosia for neurological deficits (Bisiach et al., 1986a, 1986b; Cambier et al., 1980; Cappa et al., 1987, patient no.3; Watson & Heilman, 1979, patients nos.2 and 3); and motor neglect (Schott et al., 1981; Watson & Heilman, 1979; Watson et al., 1981). Similarly, basal ganglia damage may be associated with extrapersonal visual neglect, as assessed by cancellation or bisection tasks (Damasio et al., 1980; Ferro et al., 1987; Karnath, Himmelbach, & Rorden, 2002, the putamen and the caudate nucleus; Ringman et al., 2004; Vallar & Perani, 1986, the lenticular nucleus). Personal neglect, motor neglect, and anosognosia for neurological deficits may also occur (Bisiach et al., 1986a, 1986b; Healton et al., 1982). Lesions confined to the white matter may be associated with extrapersonal visuospatial neglect (Ferro et al., 1987; Stein & Volpe, 1983). Damage to the posterior limb of the internal capsule that disrupts connections between the thalamus and the posterior cortical regions, including the posterior parietal lobe, may produce extrapersonal visual neglect (as assessed by cancellation or bisection tasks) (Bogousslavsky et al., 1988a; Decroix et al., 1986; Ferro & Kertesz, 1984; Vallar et al., 1990), personal neglect (Bogousslavsky et al., 1988a), and anosognosia for hemiplegia (Decroix et al., 1986; Vallar et al., 1990, patient no.2). Damage to the anterior limb of the internal capsule (de la Sayette et al., 1989; Viader, Cambier, & Pariser, 1982) may be associated with motor neglect, namely inability to move the contralesional limbs, in the absence of major primary motor impairments (Castaigne, Laplane, & Degos, 1970; Castaigne, Laplane, & Degos, 1972; Mark, Heilman, & Watson, 1996). Productive manifestations Delusional views concerning the contralesional side of the body (somatoparaphrenia) have been described in individual patients with lesions of the right basal ganglia (Bottini et al., 2002; Halligan, Marshall, & Wade, 1993; Healton et al., 1982), the posterior limb of the internal capsule, and, slightly, the thalamus (Nielsen, 1938). The more extensively investigated productive manifestation of neglect, drawing perseveration in cancellation tasks, is associated with subcortical damage and with cortico-subcortical lesions involving the frontal cortex (Na et al., 1999; Rusconi et al., 2002; Vallar et al., 2006). Figure 17.3 shows a severe neglect in line bisection (a) and in target cancellation (with gratuitous productions) (b) in right-brain-damaged patient F.B., who had an haemorrhagic lesion involving the basal ganglia (putamen and pallidum), the posterior limb of the internal capsule, and the corona radiata (Bottini et al., 2002). Figure 17.4 illustrates the association between subcortical and frontal damage and perseveration behaviour, with the severity of extrapersonal neglect, as indexed by omission errors, being comparable in the three patients’

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groups (Rusconi et al., 2002). The association of subcortical damage with perseveration may specifically involve the basal ganglia. This region was damaged in 25 out of 29 (89%) right-brain-damaged patients with anterior (including frontal and subcortical damage) lesions of Na et al.’s series (1999). In Rusconi et al.’s series (2002), the basal ganglia were damaged in 5 out of 11 (45%) of right-brain-damaged patients with subcortical lesions; conversely, the thalamus was damaged in two patients (18%). The effects of basal ganglia, and also of thalamic damage, as well as those of lesions of the anterior limb of the internal capsule, may involve the disruption of connections with the premotor, posterior-parietal, and superior temporal cortices (Chudasama, Baunez, & Robbins, 2003; Makris et al., 1999; Sterzi & Vallar, 1978; see Vallar, 2004, for a methodological discussion; Yeterian & Pandya, 1993, 1998). A recent anatomo-clinical correlation study in 127 left- and right-braindamaged stroke patients has shown an association between contralesional

Figure 17.3 Patient F.B. Performance in (a) line bisection and (b) line cancellation: on the right side of the sheet, F.B. spontaneously produced drawings while performing the cancellation task. (Reprinted with permission of Lippincott Williams & Wilkins: Bottini et al., 2002, Figure 2.)

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Figure 17.4 Gross anatomical correlates of drawing perseveration in left spatial neglect. Average number of perseveration (P) and omission (O) errors in 31 right-brain-damaged patients with left spatial neglect by localization of the hemispheric lesion: ANT/POST: including/sparing the frontal lobe. SUBCO: confined to subcortical structures. (Reprinted with permission of Elsevier Science Ltd: Rusconi et al., 2002, Figure 2.)

neglect in cancellation tasks, perseveration, and damage involving the basal ganglia (the caudate nucleus or the lenticular nucleus). By contrast, damage to the frontal, parietal, temporal, and occipital lobes, and to the thalamus, was not associated with perseveration (Nys et al., 2006). In sum, in patients with contralesional spatial neglect, subcortical lesions to the basal ganglia and to the frontal lobe appear to be critical sites for perseveration behaviour in cancellation tasks.

“Subcortical” neglect in the twenty-first century Nearly 30 years after the first reports on “thalamic” and “subcortical” (Healton et al., 1982; Watson & Heilman, 1979; Watson et al., 1981) neglect in man, there is definite evidence that lesions confined to the thalamus, the basal ganglia, and the white matter may be associated with manifestations of the neglect syndrome. The behavioural pattern of impairment of neglect associated with subcortical damage is not qualitatively different, basically, from the spectrum of deficits associated with cortical lesions. This conclusion (supported by both the single-case reports and the studies in large series of braindamaged patients reviewed earlier) is compatible with the view that the neural underpinnings of spatial representation and attention are cortico-subcortical circuits. According to this account, damage to one component of these net-

320 Vallar works, in addition to the disconnection effect per se (that is, defective signal transmission), also affects connected components, since damage to efferent connections produces remote effects (diaschisis: hypoperfusion and hypometabolism; see discussion in Cappa & Vallar, 1992). The relative weight of each cortical and subcortical component of the network may account for differences in the frequency and severity of the deficits associated with each lesion site, both the localization and the size of the damage being relevant factors (Hier, Mondlock, & Caplan, 1983; Kertesz & Dobrowolsky, 1981; Ringman et al., 2004; Vallar & Perani, 1986). To give one example within this connnectionist perspective, the finding that damage to the posterior limb of the internal capsule may bring about unilateral spatial neglect has been explained in terms of the interruption of pathways connecting the posterior parietal lobe with the posterior thalamus (Ferro & Kertesz, 1984; Vallar et al., 1990, patient no.2). Since the 1980s, a number of studies in brain-damaged patients have investigated whether the components of the neglect syndrome listed in Table 17.1 have different anatomical correlates. The input/output dimensions have been explored in some detail, and attempts have been made to tear apart, on the one hand, defective perceptual processing and, on the other hand, impaired premotor planning of motor responses directed toward the contralesional side of space (directional hypokinesia) (Heilman et al., 1985). The putative premotor and perceptual dichotomy has been assessed through two main types of paradigm. Some paradigms attempt to dissociate the two components by decoupling the direction of the movement of the hand from the visual control of the display. For instance, in the bisection paradigm devised by Bisiach et al. (1990), a lateral (leftward or rightward) movement of the hand brought about a movement of the pointer setting the subjective midpoint of the line in the opposite direction. Applying similar logic to a cancellation task, Tegnér and Levander (1991) and Bisiach et al. (1995) decoupled the direction of the hand movement from the patient’s visual control of the display through a 90° mirror; Nico (1996) used an epidiascope. Adair et al. (1998) and Na et al. (1998) precluded the direct view of the hand and of the target by a television monitor guiding performance. Under these conditions, patients saw a mirror-reversed display, so that, for instance, in a cancellation task, left-sided targets were seen on the right side. These paradigms, therefore, contrasted a congruent or compatible condition, in which, as in a canonical cancellation or bisection paradigm, the patient saw the actual direction of the hand movement in the visual display, with a noncongruent or incompatible condition, in which, through a device such as a pulley, a mirror, or a television monitor, the movement of the hand took place in a direction opposite to that of the relevant visual stimuli, which were seen mirror-reversed. In these paradigms, a premotor directional deficit would be characterized by the patients’ inability to perform leftward manual movements in both the congruent and non-congruent condition. A perceptual deficit, by contrast, would bring about a right-sided bias, relative to the display as seen by the patient, independent of the actual direction of the hand movement.

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Other paradigms contrasted verbal and manual responses (Bottini, Sterzi, & Vallar, 1992), or space of vision and space of manual action (Coslett et al., 1990), without introducing, however, any incompatible condition. Taken together, the studies that used non-compatible conditions (Adair et al., 1998; Bisiach et al., 1990, 1995; Na et al., 1998; Tegnér & Levander, 1991) suggest an association of the premotor pathological mechanisms of visual neglect with damage involving more anterior regions (frontal lobe, basal ganglia), and of the perceptual factors with damage involving more posterior (temporoparietal-occipital) regions. A potentially confounding factor when using noncompatible conditions is, however, the role of some working memory or executive components (Baddeley, 1996), which may become involved in the more difficult, non-congruent task, and which have been associated with frontal lobe function (see the related discussion of Fink et al., 1999). It should be noted, however, that a similar anterior–posterior dissociation has been found in paradigms which made use of congruent conditions only (Bottini et al., 1992; Coslett et al., 1990). The neglect patient F.S. (Bisiach, Berti, & Vallar, 1985), who had a right subcortical lesion involving the basal ganglia, the internal capsule, and the frontal white matter, frequently failed to react to right-sided stimuli (presented in the preserved side of space) when he had to respond by pressing a left-sided key, using the right unaffected hand. However, the role of the right posterior-inferior parietal area in some aspects of motor programming is suggested by the finding that neglect patients with damage to this region may be disproportionately slow in initiating leftward movements toward visual targets in the left side of space, while neglect patients with frontal lesions do not show such an impairment (Husain et al., 2000; Mattingley et al., 1998). A recent study in a large series of 52 right-brain-damaged patients with left neglect, with an MRI-based anatomical analysis on 29 of them, has further elucidated the role of damage to the basal ganglia in bringing about directional hypokinesia (Sapir et al., 2007). Right-brain-damaged patients with left neglect and directional hypokinesia (namely: patients who were disproportionately slow in initiating a motor response towards left-sided targets, when moving from a starting position right-sided with respect to the midsagittal plane of the body) had lesions involving the ventral lateral putamen, the claustrum, and the white matter underneath the frontal lobe. These regions, by contrast, were not damaged in patients whose latencies in initiating a motor response towards left-sided targets were unaffected by the starting position of the arm (i.e. to the left, central, or to the right of the midsagittal plane). Interestingly, only nine out of 52 patients (17%) showed the motor bias (directional hypokinesia) that was absent in 43 patients (83%). These findings suggest that, while the syndrome of spatial neglect has many aspects that may manifest in isolation (deficits of spatial attention, intention, global-local spatial processing, spatial memory and mental representation of space, see Halligan et al., 2003; Vallar, 1998, and Table 17.1), a deficit of perceptual awareness of contralesional events is a main component impairment.

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The relative contribution of perceptual and response pathological factors to visual neglect has been also assessed by another task, which requires subjects to compare the length of the two segments of pre-bisected lines (landmark task: Milner et al., 1993) with verbal or manual responses (that is, pointing to or naming the colour of the shorter-or-longer segment of the line: Bisiach et al., 1998). The choice of the contralesional segment as shorter (or of the ipsilesional segment as longer) would reflect neglect due to perceptual bias; the choice of the ipsilesional segment, both when patients are required to indicate the shorter and when they are required to indicate the longer segment, would reflect neglect due to response bias. In landmark-type tasks, there are no incompatible conditions and the response is confined to pointing or to a verbal response, rather than involving a complete leftward or rightward movement. A number of studies using landmark paradigms have suggested a distinction between perceptual and response factors in visual neglect, without providing, however, definite corresponding anatomical evidence. In one group study, frontal damage was more frequently and definitely associated with a perceptual bias, whereas a response bias was found to be more strongly associated with subcortical damage (Bisiach et al., 1998). Furthermore, the same patient may show perceptual or response biases in different tasks (Adair et al., 1998; Bisiach et al., 1998; Harvey et al., 2002; Na et al., 1998). This suggests that the issue of the “perceptual” versus “premotor” pathological mechanisms of visual neglect should be addressed through a fine-grained, componential analysis of the tasks used and of their anatomical correlates in brain-damaged patients with specific patterns of impairment. In conclusion, looking back to the 1970s, when Luigi Vignolo initiated his pioneering work on the role of subcortical structures in cognition, the definite advancement of knowledge has been that the whole spectrum of the neglect syndrome may be produced by lesions confined to right-sided subcortical structures, with the main role for the grey nuclei and their white-matter connections with relevant cortical regions. Elucidating more precisely the roles of these discrete cortico-subcortical networks, in the light of current models of spatial cognition, may be a research programme for the new century.

Acknowledgements Supported in part by a PRIN grant to G.V. I am grateful to Dr Paola Zocchi for her bibliographic help and suggestions on the history of the Padiglione Ponti of the Milan Policlinico Hospital, and to Professor Massimiliano Oliveri for a useful discussion on the remote effects of rTMS.

Note 1 Andrea Verga (1811–1895), anatomist and psychiatrist, and Serafino Biffi (1822– 1899) were two Lombard physicians, concerned with nervous and mental diseases,

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who, in the second half of the nineteenth century, had a relevant role in the foundation of the Società Freniatrica Italiana (Medea, 1954, 1960), a precursor of the Società Italiana di Neurologia.

References Adair, J. C., Na, D. L., Schwartz, R. L., & Heilman, K. M. (1998). Analysis of primary and secondary influences on spatial neglect. Brain and Cognition, 37, 351–367. Baddeley, A. D. (1996). Exploring the central executive. Quarterly Journal of Experimental Psychology, 49A, 5–28. Baron, J. C., D’Antona, R., Pantano, P., Serdaru, M., Samson, Y., & Bousser, M. G. (1986). Effects of thalamic stroke on energy metabolism of the cerebral cortex. A positron tomography study in man. Brain, 109, 1243–1259. Basso, A., Capitani, E., & Vignolo, L. A. (1979). Influence of rehabilitation on language skills in aphasic patients. A controlled study. Archives of Neurology, 36, 190–196. Berti, A., Bottini, G., Gandola, M., Pia, L., Smania, N., Stracciari, A., et al. (2005). Shared cortical anatomy for motor awareness and motor control. Science, 309, 488–491. Bird, C. M., Malhotra, P., Parton, A., Coulthard, E., Rushworth, M. F., & Husain, M. (2006). Visual neglect after right posterior cerebral artery infarction. Journal of Neurology, Neurosurgery and Psychiatry, 77, 1008–1012. Bisiach, E., Berti, A., & Vallar, G. (1985). Analogical and logical disorders underlying unilateral neglect of space. In M. I. Posner & O. S. M. Marin (Eds.), Attention and performance (vol. 11, pp. 239–246). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Bisiach, E., Bulgarelli, C., Sterzi, R., & Vallar, G. (1983). Line bisection and cognitive plasticity of unilateral neglect of space. Brain and Cognition, 2, 32–38. Bisiach, E., Cornacchia, L., Sterzi, R., & Vallar, G. (1984). Disorders of perceived auditory lateralization after lesions of the right hemisphere. Brain, 107, 37–52. Bisiach, E., Geminiani, G., Berti, A., & Rusconi, M. L. (1990). Perceptual and premotor factors of unilateral neglect. Neurology, 40, 1278–1281. Bisiach, E., & Luzzatti, C. (1978). Unilateral neglect of representational space. Cortex, 14, 129–133. Bisiach, E., Perani, D., Vallar, G., & Berti, A. (1986a). Unilateral neglect: Personal and extrapersonal. Neuropsychologia, 24, 759–767. Bisiach, E., Ricci, R., Lualdi, M., & Colombo, M. R. (1998). Perceptual and response bias in unilateral neglect: Two modified versions of the Milner landmark task. Brain and Cognition, 37, 369–386. Bisiach, E., Tegnér, R., Làdavas, E., Rusconi, M. L., Mijovi, D., & Hjaltason, H. (1995). Dissociation of ophthalmokinetic and melokinetic attention in unilateral neglect. Cerebral Cortex, 5, 439–447. Bisiach, E., & Vallar, G. (2000). Unilateral neglect in humans. In F. Boller, J. Grafman, & G. Rizzolatti (Eds.), Handbook of neuropsychology (2nd ed., vol. 1, pp. 459–502). Amsterdam: Elsevier. Bisiach, E., Vallar, G., Perani, D., Papagno, C., & Berti, A. (1986b). Unawareness of disease following lesions of the right hemisphere: Anosognosia for hemiplegia and anosognosia for hemianopia. Neuropsychologia, 24, 471–482. Bogousslavsky, J., Miklossy, J., Regli, F., Deruaz, J.-P., Assal, G., & Delaloye, B. (1988a). Subcortical neglect: Neuropsychological, SPECT, and neuropathological

324

Vallar

correlations with anterior choroidal artery infarction. Annals of Neurology, 23, 448–452. Bogousslavsky, J., Regli, F., & Uske, A. (1988b). Thalamic infarcts: Clinical syndromes, etiology, and prognosis. Neurology, 38, 837–848. Botez, M. I., Botez, T., & Oliver, M. (1985). Parietal lobe syndromes. In J. A. M. Frederiks (Ed.), Clinical neuropsychology (vol. 1, pp. 63–85). Amsterdam: Elsevier. Bottini, G., Bisiach, E., Sterzi, R., & Vallar, G. (2002). Feeling touches in someone else’s hand. Neuroreport, 13, 249–252. Bottini, G., Sterzi, R., & Vallar, G. (1992). Directional hypokinesia in spatial hemineglect. Journal of Neurology, Neurosurgery, and Psychiatry, 55, 431–436. Cambier, J., Elghozi, D., & Strube, E. (1980). Lésion du thalamus droit avec syndrome de l’hémisphère mineur. Discussion du concept de négligence thalamique. Revue Neurologique, 136, 105–116. Cambier, J., Graveleau, P., Decroix, J. P., Elghozi, D., & Masson, M. (1983). Le Syndrome de l’artère choroïdienne antérieure. Étude neuropsychologique de 4 cas. Revue Neurologique, 139, 553–559. Cappa, S. F., Papagno, C., Vallar, G., & Vignolo, L. A. (1986). Aphasia does not always follow left thalamic hemorrhage: A study of five negative cases. Cortex, 22, 639–647. Cappa, S. F., Sterzi, R., Vallar, G., & Bisiach, E. (1987). Remission of hemineglect and anosognosia during vestibular stimulation. Neuropsychologia, 25, 775–782. Cappa, S. F., & Vallar, G. (1992). Neuropsychological disorders after subcortical lesions: Implications for neural models of language and spatial attention. In G. Vallar, S. F. Cappa, & C.-W. Wallesch (Eds.), Neuropsychological disorders associated with subcortical lesions (pp. 7–41). Oxford: Oxford University Press. Carmichael, S. T., Tatsukawa, K., Katsman, D., Tsuyuguchi, N., & Kornblum, H. I. (2004). Evolution of diaschisis in a focal stroke model. Stroke, 35, 758–763. Castaigne, P., Laplane, D., & Degos, J.-D. (1970). Trois cas de négligence motrice par lésion rétro-rolandique. Revue Neurologique, 122, 234–242. Castaigne, P., Laplane, D., & Degos, J.-D. (1972). Trois cas de négligence motrice par lésion frontale pré-rolandique. Revue Neurologique, 126, 5–15. Catani, M., & ffytche, D. H. (2005). The rises and falls of disconnection syndromes. Brain, 128, 2224–2239. Chudasama, Y., Baunez, C., & Robbins, T. W. (2003). Functional disconnection of the medial prefrontal cortex and subthalamic nucleus in attentional performance: Evidence for corticosubthalamic interaction. Journal of Neuroscience, 23, 5477–5485. Cogan, D. G. (1956). Neurology of the ocular muscles. Springfield, IL: Charles C. Thomas. Colson, C., Demeurisse, G., Hublet, C., & Slachmuylder, J. L. (2001). Subcortical neglect as a consequence of a remote parieto-temporal dysfunction. A quantitative EEG study. Cortex, 37, 619–625. Coltheart, M., Patterson, K., & Marshall, J. C. (Eds.) (1980). Deep dyslexia. London: Routledge & Kegan Paul. Coslett, H. B., Bowers, D., Fitzpatrick, E., Haws, B., & Heilman, K. M. (1990). Directional hypokinesia and hemispatial inattention in neglect. Brain, 113, 475–486. Critchley, M. (1953). The parietal lobes. New York: Hafner. Damasio, A. R., Damasio, H., & Chang Chui, H. (1980). Neglect following damage to frontal lobe or basal ganglia. Neuropsychologia, 18, 123–132.

17. Subcortical neglect

325

Decroix, J. P., Graveleau, P., Masson, M., & Cambier, J. (1986). Infarction in the territory of the anterior choroidal artery. A clinical and computerized tomographic study of 16 cases. Brain, 109, 1071–1085. de la Sayette, V., Bouvard, G., Eustache, F., Chapon, F., Rivaton, F., Viader, F., et al. (1989). Infarct of the anterior limb of the right internal capsule causing left motor neglect: Case report and cerebral blood flow study. Cortex, 25, 147–154. De Renzi, E. (1967). Caratteristiche e problemi della neuropsicologia. Archivio di Psicologia, Neurologia e Psichiatria, 28, 422–440. De Renzi, E. (2001). A farewell. Cortex, 37, 5–8. Doricchi, F., & Tomaiuolo, F. (2003). The anatomy of neglect without hemianopia: A key role for parietal-frontal disconnection? Neuroreport, 14, 2239–2243. Feeney, D. M., & Baron, J.-C. (1986). Diaschisis. Stroke, 17, 817–830. Ferro, J. M., & Kertesz, A. (1984). Posterior internal capsule infarction associated with neglect. Archives of Neurology, 41, 422–424. Ferro, J. M., Kertesz, A., & Black, S. (1987). Subcortical neglect: Quantitation, anatomy, and recovery. Neurology, 37, 1487–1492. Finger, S., Koehler, P. J., & Jagella, C. (2004). The Monakow concept of diaschisis: Origins and perspectives. Archives of Neurology, 61, 283–288. Fink, G. R., Marshall, J. C., Halligan, P. W., Frith, C. D., Driver, J., Frackowiak, R. S. J., et al. (1999). The neural consequences of conflict between intention and the senses. Brain, 122, 497–512. Gaffan, D., & Hornak, J. (1997). Visual neglect in the monkey. Representation and disconnection. Brain, 120, 1647–1657. Galimberti, P. M., & Rebora, S. (Eds.) (2005). Il Policlinico. Milano e il suo ospedale. Milano: Ospedale Maggiore di Milano. Edizioni Nexo. Gall, F. J., & Spurzheim, J. K. (1810). Anatomie et physiologie du système nerveux en général et anatomie du cerveau en particulier. Paris: F. Schoell. Geschwind, N. (1965a). Disconnexion syndromes in animals and man. I. Brain, 88, 237–294. Geschwind, N. (1965b). Disconnexion syndromes in animals and man. II. Brain, 88, 585–644. Girault, J. A., Savaki, H. E., Desban, M., Glowinski, J., & Besson, M. J. (1985). Bilateral cerebral metabolic alterations following lesion of the ventromedial thalamic nucleus: mapping by the 14C-deoxyglucose method in conscious rats. Journal of Comparative Neurology, 231, 137–149. Grossi, D., & Boller, F. (1996). Sviluppo della neuropsicologia italiana moderna. In G. Denes & L. Pizzamiglio (Eds.), Manuale di neuropsicologia (2nd ed., pp. 16–34). Bologna: Zanichelli. Halligan, P. W., Fink, G. R., Marshall, J. C., & Vallar, G. (2003). Spatial cognition: Evidence from visual neglect. Trends in Cognitive Sciences, 7, 125–133. Halligan, P. W., & Marshall, J. C. (1992). Left visuo-spatial neglect: A meaningless entity? Cortex, 28, 525–535. Halligan, P. W., Marshall, J. C., & Wade, D. T. (1993). Three arms: A case study of supernumerary phantom limb after right hemisphere stroke. Journal of Neurology, Neurosurgery, and Psychiatry, 56, 159–166. Harvey, M., Kramer-McCaffery, T., Dow, L., Murphy, P. J., & Gilchrist, I. D. (2002). Categorisation of “perceptual” and “premotor” neglect patients across different tasks: Is there strong evidence for a dichotomy? Neuropsychologia, 40, 1387–1395.

326

Vallar

Healton, E. B., Navarro, C., Bressman, S., & Brust, J. C. (1982). Subcortical neglect. Neurology, 32, 776–778. Hécaen, H., Penfield, W., Bertrand, C., & Malmo, R. (1956). The syndrome of apractognosia due to lesions of the minor cerebral hemisphere. Archives of Neurology and Psychiatry, 75, 400–434. Heilman, K. M., Bowers, D., Coslett, H. B., Whelan, H., & Watson, R. T. (1985). Directional hypokinesia: Prolonged reaction times for leftward movements in patients with right hemisphere lesions and neglect. Neurology, 35, 855–859. Heilman, K. M., & Valenstein, E. (1972a). Auditory neglect in man. Archives of Neurology, 26, 32–35. Heilman, K. M., & Valenstein, E. (1972b). Frontal lobe neglect in man. Neurology, 22, 660–664. Hier, D. B., Davis, K. R., Richardson, E. P. J., & Mohr, J. P. (1977). Hypertensive putaminal hemorrhage. Annals of Neurology, 1, 152–159. Hier, D. B., Mondlock, J., & Caplan, L. R. (1983). Behavioral abnormalities after right hemisphere stroke. Neurology, 33, 337–344. Hillis, A. E., Barker, P. B., Beauchamp, N. J., Gordon, B., & Wityk, R. J. (2000). MR perfusion imaging reveals regions of hypoperfusion associated with aphasia and neglect. Neurology, 55, 782–788. Hillis, A. E., Newhart, M., Heidler, J., Barker, P. B., Herskovits, E. H., & Degaonkar, M. (2005). Anatomy of spatial attention: insights from perfusion imaging and hemispatial neglect in acute stroke. Journal of Neuroscience, 25, 3161–3167. Hillis, A. E., Wityk, R. J., Barker, P. B., Beauchamp, N. J., Gailloud, P., Murphy, K., et al. (2002). Subcortical aphasia and neglect in acute stroke: The role of cortical hypoperfusion. Brain, 125, 1094–1104. Hillis, A. E., Wityk, R. J., Barker, P. B., Ulatowski, J. A., & Jacobs, M. A. (2003). Change in perfusion in acute nondominant hemisphere stroke may be better estimated by tests of hemispatial neglect than by the National Institutes of Health Stroke Scale. Stroke, 34, 2392–2396. Husain, M., Mattingley, J. B., Rorden, C., Kennard, C., & Driver, J. (2000). Distinguishing sensory and motor biases in parietal and frontal neglect. Brain, 123, 1643–1659. Jewesbury, E. C. O. (1969). Parietal lobe syndromes. In P. J. Vinken & G. W. Bruyn (Eds.), Handbook of clinical neurology (vol. 2, pp. 680–699). Amsterdam: North Holland. Karnath, H.-O., Baier, B., & Nagele, T. (2005a). Awareness of the functioning of one’s own limbs mediated by the insular cortex? Journal of Neuroscience, 25, 7134–7138. Karnath, H.-O., Ferber, S., & Himmelbach, M. (2001). Spatial awareness is a function of the temporal not the posterior parietal lobe. Nature, 411, 950–953. Karnath, H.-O., Himmelbach, M., & Rorden, C. (2002). The subcortical anatomy of human spatial neglect: Putamen, caudate nucleus and pulvinar. Brain, 125, 350–360. Karnath, H.-O., Milner, A. D., & Vallar, G. (Eds.) (2002). The cognitive and neural bases of spatial neglect. Oxford: Oxford University Press. Karnath, H.-O., Zopf, R., Johannsen, L., Fruhmann Berger, M., Nagele, T., & Klose, U. (2005b). Normalized perfusion MRI to identify common areas of dysfunction: Patients with basal ganglia neglect. Brain, 128, 2462–2469. Kertesz, A., & Dobrowolsky, S. (1981). Right-hemisphere deficits, lesion size and location. Journal of Clinical Neuropsychology, 3, 283–299.

17. Subcortical neglect

327

Leibovitch, F. S., Black, S. E., Caldwell, C. B., Ebert, P. L., Ehrlich, L. E., & Szalai, J. P. (1998). Brain-behavior correlations in hemispatial neglect using CT and SPECT: The Sunnybrook Stroke Study. Neurology, 50, 901–908. Lichtheim, L. (1885). On aphasia. Brain, 7, 433–484. London, E. D., McKinney, M., Dam, M., Ellis, A., & Coyle, J. T. (1984). Decreased cortical glucose utilization after ibotenate lesion of the rat ventromedial globus pallidus. Journal of Cerebral Blood Flow and Metabolism, 4, 381–390. Makris, N., Meyer, J. W., Bates, J. F., Yeterian, E. H., Kennedy, D. N., & Caviness, V. S. (1999). MRI-based topographic parcellation of human cerebral white matter and nuclei. II. Rationale and applications with systematics of cerebral connectivity. NeuroImage, 9, 18–45. Mark, V. W., Heilman, K. M., & Watson, R. (1996). Motor neglect: What do we mean? Neurology, 46, 1492–1493. Marshall, J. C., & Halligan, P. W. (1995). Within- and between-task dissociations in visuo-spatial neglect: A case study. Cortex, 31, 367–376. Marshall, J. C., & Halligan, P. W. (2003). Whoever would have imagined it? Bisiach and Luzzatti (1978) on visual neglect without sight. In C. Code, C.-W. Wallesch, Y. Joanette, & A. R. Lecours (Eds.), Classic cases in neuropsychology (vol. 2, pp. 257–279). Hove: Psychology Press. Marshall, J. C., & Vallar, G. (Eds.) (2004). Spatial neglect: A Representational disorder? A Festschrift for Edoardo Bisiach. The Cortex Book Series. Milan: Masson. Masson, M., Decroix, J. P., Henin, D., Dairou, R., Graveleau, P., & Cambier, J. (1983). Syndrome de l’artère choroidienne antérieure. Étude clinique et tomodensitometrique de 4 cas. Revue Neurologique, 139, 547–552. Mattingley, J. B., Husain, M., Rorden, C., Kennard, C., & Driver, J. (1998). Motor role of human inferior parietal lobe revealed in unilateral neglect patients. Nature, 392, 179–182. Mazzocchi, F., & Vignolo, L. A. (1978). Computed assisted tomography in neuropsychological research: A simple procedure for lesion mapping. Cortex, 14, 136–144. Mazzocchi, F., & Vignolo, L. A. (1979). Localisation of lesions in aphasia: Clinical-CT scan correlations in stroke patients. Cortex, 15, 627–254. McGlinchey-Berroth, R., Bullis, D. P., Milberg, W. P., Verfaellie, M., Alexander, M., & D’Esposito, M. (1996). Assessment of neglect reveals dissociable behavioral but not neuroanatomical subtypes. Journal of the International Neuropsychological Society, 2, 441–451. Medea, E. (1954). Una grande figura della psichiatria italiana. Serafino Biffi. Rassegna di Studi Psichiatrici, 43, 1041–1046. Medea, E. (1960). Due grandi psichiatri lombardi (Andrea Verga e Serafino Biffi). Rassegna di Studi Psichiatrici, 49, 1114–1120. Mesulam, M.-M. (2002). Functional anatomy of attention and neglect: From neurons to networks. In H.-O. Karnath, A. D. Milner, & G. Vallar (Eds.), The cognitive and neural bases of spatial neglect (pp. 33–45). Oxford: Oxford University Press. Milner, A. D. (1987). Animal models for the syndrome of spatial neglect. In M. Jeannerod (Ed.), Neurophysiological and neuropsychological aspects of spatial neglect (pp. 259–288). Amsterdam: Elsevier. Milner, A. D., Harvey, M., Roberts, R. C., & Forster, S. V. (1993). Line bisection errors in visual neglect: Misguided action or size distortion? Neuropsychologia, 31, 39–49. Mort, D. J., Malhotra, P., Mannan, S. K., Rorden, C., Pambakian, A., Kennard, C., et al. (2003). The anatomy of visual neglect. Brain, 126, 1986–1997.

328

Vallar

Morton, J. (1984). Brain-based and non-brain-based models of mind. In D. Caplan, A. R. Lecours, & A. Smith (Eds.), Biological perspectives on language (pp. 40–64). Cambridge, MA: MIT Press. Na, D. L., Adair, J. C., Kang, Y., Chung, C. S., Lee, K. H., & Heilman, K. M. (1999). Motor perseverative behavior on a line cancellation task. Neurology, 52, 1569–1576. Na, D. L., Adair, J. C., Williamson, D. J., Schwartz, R. L., Haws, B., & Heilman, K. M. (1998). Dissociation of sensory-attentional from motor-intentional neglect. Journal of Neurology, Neurosurgery and Psychiatry, 64, 331–338. Nico, D. (1996). Detecting directional hypokinesia: The epidiascope technique. Neuropsychologia, 34, 471–474. Nielsen, J. M. (1938). Gerstmann syndrome: Finger agnosia, agraphia, confusion of right and left and acalculia. Archives of Neurology and Psychiatry, 39, 536–559. Nys, G. M. S., van Zandvoort, M. J., van der Worp, H. B., Kappelle, L. J., & de Haan, E. H. F. (2006). Neuropsychological and neuroanatomical correlates of perseverative responses in subacute stroke. Brain, 129, 2148–2157. Oldendorf, W. H. (1978). The quest for an image of brain: A brief historical and technical review of brain imaging techniques. Neurology, 28, 517–533. Oxbury, J. M., Campbell, D. C., & Oxbury, S. M. (1974). Unilateral spatial neglect and impairments of spatial analysis and visual perception. Brain, 97, 551–564. Patterson, K. E., Marshall, J. C., & Coltheart, M. (Eds.) (1985). Surface dyslexia. Neuropsychological and cognitive studies of phonological reading. Hove: Lawrence Erlbaum Associates Ltd. Perani, D., & Cappa, S. F. (1999). Bioimaging methods in neuropsychology. In G. Denes & L. Pizzamiglio (Eds.), Handbook of clinical and experimental neuropsychology (pp. 69–94). Hove: Psychology Press. Perani, D., Nardocci, N., & Broggi, G. (1982). Neglect after right unilateral thalamotomy. A case report. Italian Journal of Neurological Sciences, 1, 61–64. Perani, D., Vallar, G., Cappa, S., Messa, C., & Fazio, F. (1987). Aphasia and neglect after subcortical stroke. A clinical/cerebral perfusion correlation study. Brain, 110, 1211–1229. Perani, D., Vallar, G., Paulesu, E., Alberoni, M., & Fazio, F. (1993). Left and right hemisphere contribution to recovery from neglect after right hemisphere damage— an [18F]FDG pet study of two cases. Neuropsychologia, 31, 115–125. Pick, A. (1898). Beiträge zur Pathologie und pathologischen Anatomie des Centralnervensystems, mit Bemerkungen zur normalen Anatomie desselben. Berlin: Karger. Reep, R. L., Corwin, J. V., Cheatwood, J. L., Van Vleet, T. M., Heilman, K. M., & Watson, R. T. (2004). A rodent model for investigating the neurobiology of contralateral neglect. Cognitive and Behavioral Neurology, 17, 191–194. Reggia, J. (2004). Neurocomputational models of the remote effects of focal brain damage. Medical Engineering and Physics, 26, 711–722. Ringman, J. M., Saver, J. L., Woolson, R. F., Clarke, W. R., & Adams, H. P. (2004). Frequency, risk factors, anatomy, and course of unilateral neglect in an acute stroke cohort. Neurology, 63, 468–474. Rusconi, M. L., Maravita, A., Bottini, G., & Vallar, G. (2002). Is the intact side really intact? Perseverative responses in patients with unilateral neglect: A productive manifestation. Neuropsychologia, 40, 594–604. Sapir, A., Kaplan, J. B., He, B. J., & Corbetta, M. (2007). Anatomical correlates of directional hypokinesia in patients with hemispatial neglect. Journal of Neuroscience, 27, 4045–4051.

17. Subcortical neglect

329

Schmahmann, J. D. (2003). Vascular syndromes of the thalamus. Stroke, 34, 2264– 2278. Schott, B., Laurent, B., Mauguière, F., & Chazot, G. (1981). Négligence motrice par hématome thalamique droit. Revue Neurologique, 137, 447–455. Stein, S., & Volpe, B. T. (1983). Classical “parietal” neglect syndrome after subcortical right frontal lobe infarction. Neurology, 33, 797–799. Sterzi, R., Bottini, G., Celani, M. G., Righetti, E., Lamassa, M., Ricci, S., et al. (1993). Hemianopia, hemianaesthesia, and hemiplegia after left and right hemisphere damage: A hemispheric difference. Journal of Neurology, Neurosurgery, and Psychiatry, 56, 308–310. Sterzi, R., & Vallar, G. (1978). Frontal lobe syndrome as a disconnection syndrome. Acta Neurologica, 23, 419–425. Tegnér, R., & Levander, M. (1991). Through a looking glass. A new technique to demonstrate directional hypokinesia in unilateral neglect. Brain, 114, 1943–1951. Thiebaut de Schotten, M., Urbanski, M., Duffau, H., Volle, E., Levy R., Dubois B., et al. (2005). Direct evidence for a parietal-frontal pathway subserving spatial awareness in humans. Science, 309, 2226–2228. Valero-Cabré, A., Payne, B., & Pascual-Leone, A. (2007). Opposite impact on 14 C-2-deoxyglucose brain metabolism following patterns of high and low frequency repetitive transcranial magnetic stimulation in the posterior parietal cortex. Experimental Brain Research, 176, 603–615. Valero-Cabré, A., Payne, B. R., Rushmore, J., Lomber, S. G., & Pascual-Leone, A. (2005). Impact of repetitive transcranial magnetic stimulation of the parietal cortex on metabolic brain activity: A 14C-2DG tracing study in the cat. Experimental Brain Research, 163, 1–12. Vallar, G. (1993). The anatomical basis of spatial hemineglect in humans. In I. H. Robertson & J. C. Marshall (Eds.), Unilateral neglect: Clinical and experimental studies (pp. 27–59). Hove: Lawrence Erlbaum Associates Ltd. Vallar, G. (1998). Spatial hemineglect in humans. Trends in Cognitive Sciences, 2, 87–97. Vallar, G. (2000). The methodological foundations of human neuropsychology: Studies in brain-damaged patients. In F. Boller, J. Grafman, & G. Rizzolatti (Eds.), Handbook of neuropsychology (2nd ed., vol. 1, pp. 305–344). Amsterdam: Elsevier. Vallar, G. (2004). Neuroanatomy of cognition, neuroanatomy and cognition. Cortex, 40, 223–225. Vallar, G., Bottini, G., & Paulesu, E. (2003). Neglect syndromes: The role of the parietal cortex. In A. M. Siegel, R. A. Andersen, H.-J. Freund, & D. D. Spencer (Eds.), Advances in neurology. Vol. 93: The parietal lobes (pp. 293–319). Philadelphia: Lippincott Williams & Wilkins. Vallar, G., Bottini, G., Rusconi, M. L., & Sterzi, R. (1993). Exploring somatosensory hemineglect by vestibular stimulation. Brain, 116, 71–86. Vallar, G., Cappa, S. F., & Wallesch, C.-W. (Eds.) (1992). Neuropsychological disorders associated with subcortical lesions. Oxford: Oxford University Press. Vallar, G., Guariglia, C., Nico, D., & Pizzamiglio, L. (1997). Motor deficits and optokinetic stimulation in patients with left hemineglect. Neurology, 49, 1364–1370. Vallar, G., & Perani, D. (1986). The anatomy of unilateral neglect after right hemisphere stroke lesions. A clinical CT/scan correlation study in man. Neuropsychologia, 24, 609–622. Vallar, G., & Perani, D. (1987). The anatomy of spatial neglect in humans. In

330

Vallar

M. Jeannerod (Ed.), Neurophysiological and neuropsychological aspects of spatial neglect (pp. 235–258). Amsterdam: Elsevier. Vallar, G., Perani, D., Cappa, S. F., Messa, C., Lenzi, G. L., & Fazio, F. (1988). Recovery from aphasia and neglect after subcortical stroke. Journal of Neurology, Neurosurgery, and Psychiatry, 51, 1269–1276. Vallar, G., Sterzi, R., Bottini, G., Cappa, S., & Rusconi, M. L. (1990). Temporary remission of left hemianaesthesia after vestibular stimulation. Cortex, 26, 123–131. Vallar, G., Zilli, T., Gandola, M., & Bottini, G. (2006). Productive and defective impairments in the neglect syndrome: Graphic perseveration, drawing productions, and optic prism exposure. Cortex, 42, 911–920. Velasco, F., Velasco, M., Ogarrio, C., & Olvera, A. (1986). Neglect induced by thalamotomy in humans: A quantitative appraisal of the sensory and motor deficits. Neurosurgery, 19, 744–751. Viader, F., Cambier, J., & Pariser, P. (1982). Phénomène d’extinction motrice gauche. Lésion ischemique du bras antérieur de la capsule interne. Revue Neurologique, 138, 213–217. Vignolo, L. A. (1977). Le sindromi afasiche. In E. Bisiach, F. Denes, E. De Renzi, et al. (Eds.), Neuropsicologia clinica (pp. 11–42). Milano: Franco Angeli. Vilkki, J. (1984). Visual hemi-inattention after ventrolateral thalamotomy. Neuropsychologia, 22, 399–408. von Monakow, C. (1914). Die Lokalisation im Grosshirn und der Abbau der Funktion durch kortikale Herde. Wiesbaden: Bergmann. Wallesch, C.-W. (1985). Two syndromes of aphasia occurring with ischemic lesions involving the left basal ganglia. Brain and Language, 25, 357–361. Wallesch, C.-W., Kornhuber, H. H., Kunz, T., & Brunner, R. J. (1983). Neuropsychological deficits associated with small unilateral thalamic lesions. Brain, 106, 141–152. Watson, R. T., & Heilman, K. M. (1979). Thalamic neglect. Neurology, 29, 690–694. Watson, R. T., Heilman, K. M., Cauthen, J. C., & King, F. A. (1973). Neglect after cingulectomy. Neurology, 23, 1003–1007. Watson, R. T., Valenstein, E., & Heilman, K. M. (1981). Thalamic neglect. Possible role of the medial thalamus and nucleus reticularis in behavior. Archives of Neurology, 38, 501–506. Weiller, C., Ringelstein, E. B., Reiche, W., Thron, A., & Buell, U. (1990). The large striatocapsular infarct. A clinical and pathophysiological entity. Archives of Neurology, 47, 1085–1091. Weiller, C., Willmes, K., Reiche, W., Thron, A., Isensee, C., Buell, U., et al. (1993). The case of aphasia or neglect after striatocapsular infarction. Brain, 1509–1525. Wernicke, K. (1874/1966–8). The symptom complex of aphasia. Boston Studies in the Philosophy of Science. Proceedings of the Boston Colloquium for the Philosophy of Science, 4, 34–97. Witte, O. W., & Stoll, G. (1997). Delayed and remote effects of focal cortical infarctions: Secondary damage and reactive plasticity. Advances in Neurology, 73, 207–227. Yeterian, E. H., & Pandya, D. N. (1993). Striatal connections of the parietal association cortices in rhesus monkeys. Journal of Comparative Neurology, 332, 175–197. Yeterian, E. H., & Pandya, D. N. (1998). Corticostriatal connections of the superior temporal region in rhesus monkeys. Journal of Comparative Neurology, 399, 384–402.

18 Neuropsychology of attention Michael I. Posner

My work in the area of attention stems from four decades, roughly the same period as the career of Professor Vignolo. During that time, the methods and focus of studies of attention have changed, and in my view the field has become of increased interest. In the 1970s, I worked primarily on cognitive studies of attention with normal subjects, trying to characterize the mental operations involved in vigilance, selection, and conscious processing. In the 1980s, I worked with brain-injured patients to understand how lesions can selectively damage these mental operations. In the 1990s, neuroimaging techniques became available, and for the first time we could see the specific networks involved in attention. We found three, largely independent networks that were involved in achieving and maintaining the alert state, in orienting to sensory events, and in mediating among conflict. Now I have become interested in viewing one of these networks as generally related to self-regulation, a view that helps us to approach many forms of pathology. In the course of this odyssey, new methods have helped us to deepen our understanding of attention as an organic system with its own anatomy, circuitry, and pathologies. This view can integrate all of the approaches that were explored in the past, and it is of critical importance in understanding normal behavior and neurological and psychiatric disorders.

Cognitive studies of attention in the 1970s The study of attention has been a central topic from the start of human experimental psychology (James, 1890; Titchener, 1909). Generally, the focus is on probing fundamental mechanisms by training or instructing people to perform tasks that call for various attentional functions such as remaining vigilant to external events, searching for targets, processing difficult targets, or ignoring conflicting signals (Broadbent, 1958, 1971; Kahneman, 1973). In this chapter, I will try to show how work on attention changed from the 1960s to the present, as new methods became available. I am suggesting that the older methods and themes are incorporated in the new developments in a cumulative growth of the field (Posner, 1982). Although I had worked on aspects of attention all through the 1960s, my

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first major paper on the topic appeared in 1972 (Posner & Boies, 1972). It used reaction time to determine whether a pair of simultaneously presented visual letters was identical in form (e.g. AA) or in name (e.g. Aa). To study the effect of preparation, we varied the time between a visual warning signal and the letter pair that had to be matched. The brain produced a marked DC shift, called the contingent negative variation during the fore-period, which was viewed as a sign that alerting was taking place (Walter, Cooper, Aldridge, McCallum, & Winter, 1964). Reaction time improved markedly over the first 500 ms after the warning, and, as is often the case in warning signal studies, errors increased with warning interval, as though there was a trade-off between speed and accuracy. This finding suggested that warning effects did not improve the accrual of information but instead made it faster to attend to the input and thus sped the response (Posner, 1978). To study how information accrued over time, we first presented a warning signal, waited 500 ms until alerting was maximal, and then presented a single letter at fixation and observed how reaction time improved as a function of time until the second letter was presented. The reaction time showed a marked improvement over the first 150 ms. We called this an encoding function. This represented a picture of the time course of information about the first letter being absorbed, thus reducing what had to be processed from the target. A most interesting aspect of our finding was that the improvement of reaction time from a warning signal (alerting) and improvement due to encoding the first letter were independent. The amount of improvement due to a warning signal alone and the amount of improvement from a first letter added up to the total improvement when the letter served as both a warning signal and as an item to be encoded. Hebb (1949) had suggested that all stimuli had two effects on the nervous system. One effect was to act upon the reticular activating system to arouse the organism, and the other was to deliver information over the great sensory pathways. Our finding provided an example of how a separate physiology may lead to independent effects on response time. Apparently, no one else has found this exciting observation, since there is almost no reference to this finding in the voluminous literature on attention. However, the finding that manipulating a different independent variable produces additive effects on reaction time (Sternberg, 1969) may be interpreted as supporting this view. Recently, a student of psychology at the University of Oregon (USA) replicated additivity between encoding and alerting in a completely different task (Kanske, 2004). In 1972, we did not realize that alerting had its primary influence via norepinephrine pathways on the dorsal visual system (Morrison & Foote, 1986), while encoding of the first letter had its effect upon the ventral visual pathway. This physiological finding is probably very important in understanding why these two functions are independent. Of course, there are connections between the ventral and dorsal pathway, so that the anatomy alone does not ensure independence. For this reason, convergence between the physiological and behavioral studies provides an important perspective

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on at least one situation in which anatomical separation implies a remarkable degree of behavioral independence. A second finding of the 1972 paper was the time course of interference between letter matching and a secondary task of pressing a key as rapidly as possible to the onset of a tone. We found that there was no interference during the encoding function, but subsequent to the target letter, there was massive interference with the tone. This finding, that encoding can occur without attention, has now become commonplace after many studies of masking a prime (e.g. Dehaene, 2004; Marcel, 1983). In these studies, the prime facilitates processing of a subsequent target even when masking makes the prime unconscious. In the 1970s, these studies were regarded as functional studies of attention with little or no connection to brain systems. The idea was that cognitive processes are best described in software terms and that the hardware made little or no important difference. Many in cognitive psychology thought that studies of the brain could not in principle help us to understand cognitive processes. Even then, Professor Vignolo and other neuropsychologists, who studied brain damage, had little patience with this separation. It was just too clear that brain damage impaired cognition in systematic ways.

Neuropsychological studies in the 1980s In 1979, I began to work on making systematic connections between brain systems and attention. I was studying the use of a cue in an otherwise empty visual field as a way of moving attention to a target (Posner, 1980). Electrodes near the eyes were used to ensure there were no eye movements, and since only one response was required, there was no way to prepare the response differently depending upon the cue, making it clear that whatever changes were induced by the cue were covert and not due to motor adjustment of the eyes or hand. It was found that covert shifts could enhance the speed of responding to the target even in a nearly empty field. Within half a second, one could shift attention to a visual event and, when it indicated a likely target at another location, move attention to enhance processing at the new location. We had trapped a covert attention shift and observed its movement. In fact, three students (Shulman, Remington, & McLean, 1979) showed that response times to probes at intermediate locations are enhanced at intermediate times as though attention actually moved through the space. Whether attention moves through the intermediate space is still a disputed matter (LaBerge, 1995), suggesting the limitation of purely behavioral studies. At the time, it was also hard to understand how a movement of attention could possibly be executed by neurons. Subsequently, it was shown that the population vector of a set of neurons in the motor system of a monkey could carry out what would appear, behaviorally, as a mental rotation (Georgopoulos, Lurito, Petrides, Schwartz, & Massey, 1989). After that finding, a covert shift of attention did not seem too far-fetched.

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About this time, I became aware of a number of papers using intracellular recording to study the properties of cells in the posterior parietal lobe of the monkey (Mountcastle, 1978; Wurtz, Goldberg, & Robinson, 1980). These papers suggested the possibility of attention cells in the parietal cortex that might be critically involved in orienting attention toward visual events. A Tuesday night meeting of our research group had been assigned to read these papers. I asked whether we were measuring with reaction time, behavior that results from such attention cells. I thought that if the covert shifts of attention in man could be connected with the monkey studies, it might contribute to linking cognitive psychology to brain mechanisms. I do not think there was much enthusiasm for this idea at the time. After all, cognition was about software, and what did it have to do with the parts of the brain in which cells were found in the monkey? In 1979, I met Oscar Marin, an outstanding behavioral neurologist. He was about to move to Portland, Oregon, to set up a service and research effort at Good Samaritan Hospital, and he invited me to set up a neuropsychological laboratory in conjunction with the hospital. It was a perfect time for me because I had spent the first 6 months of 1979 in New York working with Michael Gazzaniga, whose career in psychology is probably familiar to most readers, and my brother Jerry Posner, who is a world-leading neurologist. I tested mostly patients with lesions of the parietal lobe. Gazzaniga had reported that such patients could make same-different judgments concerning objects that they were unable to report consciously (Volpe, LeDoux, & Gazzaniga, 1979). That seemed like something that could be followed up in more analytic cognitive studies. What did a right-parietal lesion do that made access to material on the left side difficult or impossible for consciousness but still left the information available for other judgments? This is the question I pursued in the new laboratory in Portland. In the end, I commuted to Portland once a week for 7 years. It was such a pleasure to work with Dr Marin that the long drive was worthwhile. These studies overlapped those of Prof. Vignolo, because most of them concerned patients who suffered from some form of neglect, resulting from lesions produced by strokes. The results were, for me, a revelation. Patients with different lesion localizations in the parietal lobe, the pulvinar, and the colliculus all tended to show neglect of the side of space opposite the lesion. But in a detailed cognitive analysis, it was clear that they differed in showing deficits in specific mental operations involved in shifting attention (Posner, 1988). As I saw it at the time, we had found a new form of brain localization. Different brain areas executed individual mental operations or computations such as disengaging from the current focus of attention (parietal lobe), moving or changing the index of attention (colliculus), and engaging the subsequent target (pulvinar). No wonder, Lashley thought the whole brain was involved in mental tasks. It was not the whole brain, but a widely dispersed network of quite localized neural areas. Even looking back from the perspective of 20 years, I can again feel the excitement I had surrounding this idea at the time.

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As a result of these findings, I moved on to neuroimaging studies of normal persons. This was not any kind of rejection of the importance of patient studies, but rather a desire to be able to see whether the same separation of mental operations could be observed by neuroimaging in normal persons. Lesion studies remain important in the era of neuroimaging. Damage to the network can often show that some computation is essential to the cognitive process. In turn, neuroimaging also improves the prospects for patient work, not only in helping localization of lesions, but also by providing an excellent means of synthesizing therapies that might affect different parts of a network into a more optimal treatment (Mayberg, 2003).

Neuroimaging and attention in the 1990s I read an article in Scientific American (Lassen, Ingvar, & Skinhoj, 1978) indicating that cerebral blood flow changes in the brain when a person reads silently. In cognitive psychology, reading had been well studied. We knew something about the orthographic, phonological, and semantic operations that must have taken place in reading, but they would be combined in the overall blood flow during the reading of passages. Even more compelling for the possible anatomy of mental operations was a paper published in 1985 by Per Roland (Roland & Friberg, 1985), indicating that different parts of the brain are active during tasks such as finding a route, carrying out mental arithmetic, and making verbal descriptions. However, even in this paper, there was no effort to uncover the specific operations that might be performed by the brain areas involved. About this time, the Washington University School of Medicine, in St Louis, Missouri, USA, started a national search for a psychologist who might work in conjunction with the developing positron emission tomography (PET) center led by Marc Raichle. It might be surprising to people how reluctant psychologists were to take a chance on brain imaging. For me, this was the opportunity to test the idea arising from the neurological studies that individual mental operations are localized in separate brain tissue. Raichle and his colleagues at Washington University recognized the importance of being able to use PET to illuminate questions of higher brain function. The studies at Washington University did quite a lot for the development of neuroimaging and, in the main, supported the idea that widely scattered brain areas are involved when any task is performed (Posner & Raichle, 1994, 1998). Some people thought that these areas are specific for domains of function such as language or face stimuli. I have maintained the importance of mental operations, without denying that domain specificity may also play a role in localization (Posner, 2004). For example, in the area of face processing, there has been a lot of dispute over whether there is a specific face area because experts in other domains activate the same area when thinking about their domain of expertise. However, if one thinks about localization of mental

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operations, it seems clear that faces and other objects, by which we come to recognize individuals, via fine distinctions, share operations in common. A similar argument has recently been applied to the visual word form area (McCandliss, Cohen, & Dehaene, 2003). I had gone to Washington University in the hope of pursuing work on attention. When I talked to neurologists about covert shifts of attention (without eye movements) and then proposed to break the invisible shift into component operations such as disengaging and moving, I saw eyes glaze and interest wane. Language studies have the advantage that the operations are more concrete and that neurosurgeons value knowledge about the localization of language areas to aid them in avoiding such areas during surgery. Our language studies (Petersen, Fox, Posner, Mintun, & Raichle, 1989; Posner, Petersen, Fox, & Raichle, 1988) did indicate some brain areas that appear to be involved in attention. Together with the lesion studies we had already done, it was sufficient to lead us to develop a neural network view of attention (Posner & Petersen, 1990). The imaging group at Washington University was able to recruit Maurzio Corbetta and Gordon Shulman, who have carried out attention studies, better designed than I ever could have done. My reading of their fascinating review paper (Corbetta & Shulman, 2002) suggests that there is localization of quite separate mental operations within two areas of the parietal lobe that form a portion of a larger network whose function is to align attention with the target. Although my initial speculation of which operations were important may not have been correct, the beautifully localized brain areas support the overall localization hypothesis. In our overview of attention in 1990, we had argued that the brain network supporting orienting to sensory events (what we called the posterior attention system) is separate from a second, more executive attention system that is activated when people have to select among responses or concentrate on information in memory. In an effort to test this idea, a PET study was conducted of the Stroop effect (Pardo, Pardo, Janer, & Raichle, 1990). This task activated several frontal areas, including the anterior cingulate. The study of this system became a focus of my more recent work discussed below (Fan, Flombaum, McCandliss, Thomas, & Posner, 2003).

Self-regulation 2000 Self-regulation has been a central concept in developmental psychology and in the study of psychopathology. A recent paper by Fonagy and Target (2002) says: “Self-regulation is the key mediator between genetic predisposition, early experience and adult functioning.” In their view, self-regulation refers to children’s (1) ability to control the reaction to stress, (2) capacity to maintain focused attention, and (3) capacity to interpret mental states in themselves and others. Self-regulation is also an obvious feature of normal socialization apparent

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to caregivers, teachers, and others who work with children. A recent historical prospective and review of self-regulation (Bronson, 2000) outlined perspectives from psychoanalysis, social learning theory, Vygotsky, Piaget (including neo-Piagetians), and the information-processing tradition. Each of these approaches seeks to account for how children achieve the ability to regulate their emotions and, to a certain extent, their thought processes. Imaging In previous work, we have stressed that some brain networks provide control operations that facilitate or inhibit the functions of other networks, providing a neural basis for self-regulation (Posner & Rothbart, 1998, 2000). For example, different parts of the cingulate gyrus are involved in cognitive and emotional monitoring processes. Areas of the dorsal anterior cingulate are highly interconnected with lateral frontal and parietal structures and become very active when a task requires selection among conflicting alternatives (Botvinick, Braver, Barch, Carter, & Cohen, 2001; Bush, Luu, & Posner, 2000). More ventral areas of the cingulate in conjunction with other limbic structures (e.g. the amygdala) provide the basis for regulation of emotion (Bush et al., 2000; Drevets & Raichle, 1998). Despite these important advances, it is still a major task to isolate by neuroimaging the neural networks responsible for self-regulation in order to be able to observe how genes and the environment regulate them during development. The anterior cingulate gyrus, one of the main nodes of the executive attention network, has been linked to a variety of specific functions in attention (Posner & Fan, in press), working memory (Duncan et al., 2000), emotion (Bush et al., 2000), pain (Rainville, Duncan, Price, Carrier, & Bushnell, 1997), monitoring for conflict (Botvinick et al., 2001), and error (Holroyd & Coles, 2002). These functions have been well documented, but no single rubric seems to explain all of them. In emotional studies, the cingulate is often seen as part of a network involving orbital frontal and limbic (amygdala) structures. The frontal areas seem to have an ability to interact with the limbic system (Davidson, Putnam, & Larson, 2000) in a manner that could fit well with selfregulation. A specific test for this idea involved exposure to erotic films, with the requirement to regulate any resulting arousal. The cingulate activity shown by functional magnetic resonance imaging (fMRI) was found to be related to the regulatory instruction (Beauregard, Levesque, & Bourgouin, 2001). In a different study, cognitive reappraisal of photographs producing negative affect showed a correlation between cingulate activity and the reduction in negative affect (Ochsner, Bunge, Gross & Gabrieli, 2002). Similarly, in a study in which hypnotism was used to control the perception of pain, the cingulate activity reflected the perception, not the strength, of the physical stimulus (Rainville et al., 1997). These results show a role for this anatomical structure in regulating limbic activity related to emotion and provide evidence for a role

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of the cingulate as a part of the network involved in self-regulation (Bush et al., 2000). In tasks like the Stroop and flanker, conflict is introduced by the need to respond to one aspect of the stimulus while ignoring another (Bush et al., 2000; Fan et al., 2003). Cognitive activity that involves this kind of conflict activates the dorsal anterior cingulate and lateral prefrontal cortex. Large lesions of the anterior cingulate, in either adults (Damasio, 1994) or children (Anderson, Damasio, Tranel, & Damasio, 2000), result in great difficulty in regulating behavior, particularly in social situations. Smaller lesions may produce only a temporary inability to deal with conflict in cognitive tasks (Ochsner et al., 2001; Turken & Swick, 1999). Development The importance of being able to study the emergence of executive attention is enhanced because cognitive measures of conflict resolution in these laboratory tasks have been linked to aspects of children’s temperament. Signs of development of executive attention provoked by cognitive tasks relate to a temperamental measure, obtained from caregiver reports, which is called effortful control (Gerardi-Caulton, 2000; Rothbart, Ellis, & Posner, 2004). Children relatively less affected by conflict received higher parental ratings of temperamental effortful control and higher scores on laboratory measures of inhibitory control (Gerardi-Caulton, 2000). We regard effortful control as reflecting the efficiency with which the executive attention network operates in naturalistic settings. Empathy is strongly related to effortful control; thus, children with high ratings of effortful control show greater empathy (Rothbart, Ahadi, & Hershey, 1994). To display empathy for others requires that we interpret their signals of distress or pleasure. Imaging work in normal subjects shows that sad faces activate the amygdala. As sadness increases, this activation is accompanied by activity in the anterior cingulate as part of the attention network (Blair, Morris, Frith, Perrett, & Dolan, 1999). It seems likely that the cingulate activity represents the basis for our attention to the distress of others. Developmental studies have identified different routes to the successful development of conscience. The internalization of moral principles appears to be facilitated in fearful preschool-aged children, especially when their mothers use gentle discipline (Kochanska, 1995). A strongly reactive amygdala would provide the signals of distress that would easily allow empathic feelings for others and improve socialization abilities. In the absence of this form of control, development of the cingulate would allow appropriate attention to the signals provided by amygdala activity. Consistent with its influence on empathy, effortful control also appears to play a role in the development of conscience. In addition, internalized control is facilitated in children with high effortful control (Kochanska, Murray, Jacques, Koenig, & Vandegeest,

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1996). Thus, two separable control systems, one reactive (fear) and one self-regulative (effortful control), appear to regulate the development of conscience. Genes and experience Almost all studies of attention have been concerned with either general abilities or the effects of brain injury or disease on attention. However, it is clear that normal individuals differ in their ability to attend to sensory events and even more clearly in their ability to concentrate for long periods on internal trains of thought. To study these individual differences, we have developed an attention network test that examines the efficiency of the three brain networks we have described above (Fan, McCandliss, Sommer, Raz, & Posner, 2002). The data provide three numbers representing the skill of each individual in the alerting, orienting, and executive networks. In a sample of 40 normal persons, we found each of these indexes to be reliable over repeated testing; in addition, no correlation between them was found. The ability to measure individual differences in attention among adults raises the question of the degree to which attention is heritable. To address this issue, we used our attention network test to study 26 pairs of monozygotic and 26 pairs of dizygotic same-sex twins (Fan, Wu, Fossella, & Posner, 2001). We found strong correlations between the monozygotic twins for the executive network measure. This led to an estimate of heritability of the executive network of .89. Because of the small sample, the estimate of 95% confidence interval for heritability is between .3 and .9. Nonetheless, these data support a role for genes in the efficacy with which the executive network is put into action. As a way of searching for candidate genes that might relate to the efficiency of these networks, we used the association of the executive network with the neuromodulator dopamine (Fossella, Posner, Fan, Swanson, & Pfaff, 2002). To do this, we ran 200 subjects in the Association Network Test (ANT) and genotyped them to examine frequent polymorphisms in genes related to their respective neuromodulators. We found significant association of two genes related to dopamine, the dopamine receptor D4 (DRD4) and monoamine oxidase A (MAOA) genes. We then conducted a neuroimaging experiment in which we compared persons with two different alleles of these two genes while they performed the ANT. We found that these alleles produced different activation within the anterior cingulate, which is a major node of this network (Fan et al., 2003). A central aspect of the executive attention network is the ability to deal with conflict. We used this feature to design a set of training exercises that were adapted from efforts to send macaque monkeys into outer space (Rumbaugh & Washburn, 1995). These exercises resulted in monkeys’ ability to resolve conflict in a Stroop-like task (Washburn, 1994). Our exercises began with training the child to control the movement of a cat by using a

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joystick as well as prediction of where an object would move, given its initial trajectory. Other exercises emphasized the use of working memory to retain information for a matching to sample task and the resolution of conflict. We have tested the efficacy of a very brief, 5-day attention training with groups of 4-year-old children. The children were brought to the laboratory for 7 days for sessions lasting about 40 minutes. These sessions were conducted over a 2–3-week period. The first and last days were used to assess the effects of the training by use of the child version of the attention network test (ANT) (Rueda et al., 2004a); a general test of intelligence, the Kaufman Brief Intelligence Test (K-BIT) (Kaufman & Kaufman, 1990); and a temperament scale (the Children Behavior Questionnaire (CBQ)). During the administration of the ANT, we recorded 128 channels of electroencephalogram (EEG) in order to observe the amplitude and time course of activation of the anterior cingulate (Rueda, Posner, Rothbart, & Davis-Stober, 2004b). During our first experiment, we compared 12 children who underwent our training procedure with 12 who were randomly selected and took no training, but came in twice for assessment. In our second experiment, we again investigated 4-year-olds, but the control group came in seven times and saw videos that required an occasional response on their part to keep them playing. All of the children seemed to enjoy the experience, and their caregivers were quite supportive of the effort. In this chapter, we present only a brief overview of our initial results. A more detailed account will appear elsewhere (Rueda, Rothbart, McCandliss, Saccamanno, & Posner, 2005). Of course, 5 days is a minimal amount of training to influence the development of networks that develop for many years. Nonetheless, we found that the EEG of the experimental group showed more adult-like activity following training, particularly in the N2 component known to reflect the anterior cingulate response to conflict in this task (Rueda et al., 2004b; van Veen & Carter, 2002). There was also a general improvement in intelligence in the experimental group as measured by the K-BIT. We did not observe changes in temperament over the course of the training. As the number of children who undergo our training increases, we can examine aspects of their temperament and genotype to help us understand who might benefit from attention training. To this end, we are currently genotyping all of the children in an effort to examine the candidate genes found previously to be related to the efficacy of the executive attention networks. We are also beginning to examine the precursors of executive attention in even younger children, with the goal of determining whether there is a sensitive period during which interventions might prove most effective. There is already some evidence in the literature about older children who suffer from attention deficit hyperactivity disorder (ADHD) that using attention training methods can produce improvement in the ability to concentrate and in general intelligence (Kerns, Esso, & Thompson, 1999; Klingberg, Forssberg, & Westerberg, 2002; Shavlev, Tsal, & Mevorach, 2003). As a result, we are also working with other groups to carry out these exercises in

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children with learning-related problems such as ADHD and autism. These projects will test whether the programs are efficacious with children who have special difficulties with attention as part of their disorder. We hope also to have some preschools adopt attention training as a specific part of their preschool curriculum. This would allow training over more extensive time periods and testing of other forms of training such as in social groups (Mills & Mills, 2000). While we do not yet know whether our specific program is optimal, we believe that the evidence we have obtained for the development of specific brain networks during early childhood provides a strong rationale for sustained efforts to see whether we can improve the attentional abilities of children. In addition, it would be possible to determine how well such methods might generalize to the learning of the wide variety of skills that must be acquired during school. Psychopathology Many neurological and psychiatric disorders, including neglect, Alzheimer’s dementia, autism, schizophrenia, and ADHD, have been said to involve pathologies of attention. Some of these represent disorders studied in neurology, and others would be called psychiatric. However, without a real understanding of the neural substrates of attention, this has been a somewhat empty classification. This situation is changed with the systematic application of our understanding of attentional networks to pathological issues. Only a few pathologies have been studied by methods which allow us to state which of the attention networks are affected; more commonly, one or another of the attentional networks has been examined in isolation. Neglect Lesions of the temporal parietal junction most often produce a strong tendency to miss stimuli that are presented on the side of space opposite to the lesion. Two networks have been shown to be functioning abnormally in patients with this syndrome. They have difficulty in orienting to stimuli on the side of space opposite to the lesion (Posner, Walker, Friedrich, & Rafal, 1984), and they show a strong deficit in maintaining the alert state in the absence of a warning signal (Robertson, Mattingley, Rorden, & Driver, 1998). Some data suggest that left-hemisphere lesions produce the first symptom, but not the second (Posner, 1988), making it possible to dissociate the two networks in these patients. Normal and pathological aging A recent study using the ANT showed that normal aging produces difficulty in maintaining the alert state. This difficulty is also shown by early Alzheimer’s

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disease patients (Fernandez-Duque & Black, 2006). However, these patients show widespread deficits, including the orienting (Parasuraman, Greenwood, Haxby, & Grady, 1992) and the executive networks (Fernandez-Duque & Black, 2006). As might be expected, general processes, such as aging and Alzheimer’s disease, that affect much of the brain, produce widespread attentional problems in all networks. Autism Autism is a disorder that has been linked to the orienting system. It is well known that autistic persons do not normally orient to faces. However, many studies show their difficulty in orienting in tasks that involve nonsocial stimuli similar to those used in the ANT (Akshoomoff, Pierce, & Courchesne, 2002; Rodier, 2002). Similar deficits in the ability to disengage and move attention have been reported in autism in relation to abnormal development of the cerebellum (Akshoomoff et al., 2002). We do not know whether this abnormality is due only to cerebellar deficits, since many of the patients also show parietal abnormalities. Rodier (2002) has some evidence that the abnormalities found in autism might relate to a gene associated with migration of cells in early development. Schizophrenia A number of years ago, we tested never-medicated schizophrenic patients with a cued detection task similar to the orienting part of the ANT. At rest, these subjects had a focal decrease in cerebral blood flow in the left globus palidus (Early, Posner, Reiman, & Raichle, 1989), a part of the basal ganglia with close ties to the anterior cingulate. The subjects showed a deficit in orienting similar to what we had observed in left parietal patients (Early et al., 1989). When their visual attention was engaged, they had difficulty in shifting attention to the right visual field. This deficit in orienting has been replicated in first-break schizophrenics, but does not seem to be true later in the disorder (Maruff, Currie, Hay, McArthur-Jackson, & Malone, 1995), nor does this pattern appear to be part of the genetic predisposition to schizophrenia (Pardo et al., 2000). Since first-break schizophrenics run in our study (Early et al., 1989) also showed deficits in conflict tasks, particularly when they had to rely on a language cue, we concluded that the overall pattern of their behavior was most consistent with a deficit in the anterior cingulate and basal ganglia, parts of a frontally based executive attention system (Benes, 1999). A more recent paper using the ANT shows this more clearly: a large deficit in the executive network (Wang, Fan, Dong, Wang, Lee, & Posner, 2005) and a much smaller deficit in orienting.

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Borderline personality disorder Borderline personality disorder is characterized by very great lability of affect and problems in interpersonal relations. In some cases, patients are suicidal and carry out self-mutilation. Because this diagnosis has been studied largely by psychoanalysts and has a very complex definition, it might at first be regarded as a poor candidate for specific pathophysiology involving attentional networks. However, we focused on the temperamentally based core symptoms of the disorder, which are extreme negative emotionality and difficulty in self-regulation. We found that patients were very high in negative affect and relatively low in effortful control (Rothbart, Ahadi, & Evans, 2000), and defined a temperamentally matched control group of normal persons without a personality disorder who were equivalent in these two dimensions. Our study with the ANT found a specific deficit in the executive attention network in borderline patients (Posner, Rothbart, Vizueta, Levy, Thomas, & Clarkin, 2002; Posner et al., 2003). Preliminary imaging results suggested overgeneralization of responding in the amygdala and reduced responding in the anterior cingulate and related midline frontal areas (Posner et al., 2002, 2003). Patients with higher effortful control and lower conflict scores on the ANT were also the most likely to show the effects of therapy. This methodology shows the utility of focusing on the core deficits of patients, defining appropriate control groups based on matched temperament, and using specific attentional tests to help determine how to conduct imaging studies. Although attentional deficits might not be fully diagnostic for these disorders, the patterns frequently differ between pathologies. I believe that these links between attention and various pathologies provide support for a more general use of neuropsychology in understanding and remediating psychopathologies (Mayberg, 2003).

Looking to the future The work on attention discussed in this chapter represents a cumulative development (Posner, 1982). The emphasis on self-regulation rests upon the network theory developed from imaging studies, which in turn uses cognitive tasks for activating brain networks. Current efforts are attempting to use neuroimaging to link together studies of the role of attention in normal and pathological development to the role of genes and experience in shaping the underlying networks (Posner, 2004). These efforts should advance the role of neuropsychology in the understanding and treatment of patients.

References Akshoomoff, N., Pierce, K., & Courchesne, E. (2002). The neurobiological basis of autism from a developmental perspective. Development and Psychopathology, 14, 613–634.

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Anderson, S. W., Damasio, H., Tranel, D., & Damasio, A. R. (2000). Long-term sequelae of prefrontal cortex damage acquired in early childhood. Developmental Neuropsychology, 18, 281–296. Beauregard, M., Levesque, J., & Bourgouin, P. (2001). Neural correlates of conscious self-regulation of emotion. Journal of Neuroscience, 21 (RC 165), 1–6. Benes, F. (1999). Model generation and testing to probe neural circuitry in the cingulate cortex of postmortem schizophrenic brains. Schizophrenia Bulletin, 24, 219–229. Blair, R. J. R., Morris, J. S., Frith, C. D., Perrett, D. I., & Dolan, R. J. (1999). Dissociable neural responses to facile expression of sadness and anger. Brain, 1222, 883–893. Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., & Cohen, J. D. (2001). Conflict monitoring and cognitive control. Psychological Review, 108, 624–652. Broadbent, D. E. (1958). Perception and communication. London: Pergamon. Broadbent, D. E. (1971). Decision and stress. New York: Academic Press. Bronson, M. B. (2000). Self-regulation in early childhood. New York: Guilford Press. Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and emotional influences in the anterior cingulate cortex. Trends in Cognitive Science, 4/6, 215–222. Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews, Neuroscience, 3, 201–215. Damasio, A. (1994). Descartes’ error: Emotion, reason and the brain. New York: G.P. Putnam. Davidson, R. J., Putnam, K. M., & Larson, C. L. (2000). Dysfunction in the neural circuitry of emotion regulation: A possible prelude to violence. Science, 289, 591–594. Dehaene, S. (2004). The neural basis of subliminal priming. In N. Kanwisher & J. Duncan (Eds.), Functional neuroimaging of visual cognition. Attention and Performance Series XX (pp. 205–224). Oxford: Oxford University Press. Drevets, W. C., & Raichle, M. E. (1998). Reciprocal suppression of regional blood flow during emotional versus higher cognitive processes: Implications for interactions between emotion and cognition. Cognition and Emotion, 12, 353–285. Duncan, J., Seitz, R. J., Kolodny, J., Bor, D., Herzog, H., Ahmed, A., et al. (2000). A neural basis for general intelligence. Science, 289, 457–460. Early, T. S., Posner, M. I., Reiman, E. M., & Raichle, M. E. (1989). Hyperactivity of the left stiato-pallidal projection. I. Lower level theory. Psychiatric Developments, 2, 85–108. Fan, J., Flombaum, J. I., McCandliss, B. D., Thomas, K. M., & Posner, M. I. (2003). Cognitive and brain mechanisms of conflict. NeuroImage, 18, 42–57. Fan, J., McCandliss, B. D., Sommer, T., Raz, M., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14, 340–347. Fan, J., Wu, Y., Fossella, J., & Posner, M. I. (2001). Assessing the heritability of attentional networks. Bio-Medical Central Neuroscience, 2, 14. Fernandez-Duque, D., & Black, S. E. (2006). Attentional networks in normal aging and Alzheimer’s disease. Neuropsychology, 20, 133–143. Fonagy, P., & Target, M. (2002). Early intervention and the development of selfregulation. Psychoanalytic Quarterly, 22, 307–335. Fossella, J., Posner, M. I., Fan, J., Swanson, J. M., & Pfaff, D. M. (2002). Attentional phenotypes for the analysis of higher mental function. Scientific World Journal, 2, 217–223.

18. Neuropsychology of attention

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Georgopoulos, A. P., Lurito, J. T., Petrides, M., Schwartz, A. B., & Massey, J. T. (1989). Mental rotation of the neuronal population vector. Science, 243, 234–236. Gerardi-Caulton, G. (2000). Sensitivity to spatial conflict and the development of selfregulation in children 24–36 months of age. Developmental Science, 3/4, 397–404. Hebb, D. O. (1949). Organization of behavior. New York: Wiley. Holroyd, C. B., & Coles, M. G. H. (2002). The neural basis of human error processing: Reinforcement learning, dopamine and the error related negativity. Psychological Review, 109, 679–709. James, W. (1890). Principles of psychology. New York: Holt. Kahneman, D. (1973). Attention and effort. Englewood Cliffs, NJ: Prentice-Hall. Kanske, P. (2004). Studies of alerting and encoding. Unpublished paper, University of Oregon, Eugene. Kaufman, A. S., & Kaufman, N. L. (1990). Kaufman Brief Intelligence Test—manual. Circle Pines, MN: American Guidance Service. Kerns, K. A., Esso, K., & Thompson, J. (1999). Investigation of a direct intervention for improving attention in young children with ADHD. Developmental Neuropsychology, 16, 273–295. Klingberg, T., Forssberg, H., & Westerberg, H. (2002). Training of working memory in children with ADHD. Journal of Clinical and Experimental Neuropsychology, 24, 781–791. Kochanska, G. (1995). Children’s temperament, mothers’ discipline, and security of attachment: Multiple pathways to emerging internalization. Child Development, 66, 597–615. Kochanska, G., Murray, K., Jacques, T. Y., Koenig, A. L., & Vandegeest, K. A. (1996). Inhibitory control in young children and its role in emerging internationalization. Child Development, 67, 490–507. LaBerge, D. (1995). Attentional processing. Cambridge, MA: Harvard University Press. Lassen, N. A., Ingvar, D. H., & Skinhoj, E., (1978). Brain function and blood flow. Scientific American, 238, 62–71. Marcel, A. J. (1983). Conscious and unconscious perception: Experiments on visual masking and word recognition. Cognitive Psychology, 15, 197–237. Maruff, P., Currie, J., Hay, D., McArthur-Jackson, C., & Malone, V. (1995). Asymmetries in the covert orienting of visual spatial attention in schizophrenia. Neuropsychologia, 31, 1205–1223. Mayberg, H. S. (2003). Modulating dysfunctional limbic-cortical circuits in depression: Towards development of brain-based algorithms for diagnosis and optimized treatment. British Medical Bulletin, 65, 193–207. McCandliss, B. D., Cohen, L., & Dehaene, S. (2003). The visual word form area: Expertise for reading in the fusiform gyrus. Trends in Cognitive Neuroscience, 7, 293–299. Mills, D., & Mills, C. (2000). Hungarian kindergarten curriculum translation. London: Mills Production Limited. Morrison, J. H., & Foote, S. L. (1986). Noradrenergic and serotoninergic innervation of cortical, thalamic and tectal visual structures in Old and New World monkeys. Journal of Comparative Neuorology, 243, 117–128. Mountcastle, V. B. (1978). The world around us: Neural command functions for selective attention. Neuroscience Research Progress Bulletin, 14 (Suppl.), 1–47. Ochsner, K. N., Bunge, S. A., Gross, J. J., & Gabrieli, J. D. E. (2002). Rethinking

346

Posner

feelings: An fMRI study of the cognitive regulation of emotion. Journal of Cognitive Neuroscience, 14, 1215–1229. Ochsner, K. N., Kosslyn, S. M., Cosgrove, G. R., Cassem, E. H., Price, B. H., Nierenberg, A. A., et al. (2001). Deficits in visual cognition and attention following bilateral anterior cingulotomy. Neuropsychologia, 39, 219–230. Parasuraman, R., Greenwood, P. M., Haxby, J. V., & Grady, C. L. (1992). Visuospatial attention in dementia of the Alzheimer type. Brain, 115, 711–733. Pardo, J. V., Pardo, P. J., Janer, K. W., & Raichle, M. E. (1990). The anterior cingulate cortex mediates selection in the Stroop attentional conflict paradigm. Proceedings of the National Academy of Sciences of the USA, 87, 256–259. Pardo, P. J., et al. (2000). Genetic and state variables of neurocognitive dysfunction in schizophrenia: A twin study. Schizophrenia Bulletin, 26, 459–477. Petersen, S. E., Fox, P. T., Posner, M. I., Mintun, M., & Raichle, M. E. (1989). Positron emission tomographic studies of the processing of single words. Journal of Cognitive Neuroscience, 1, 153–170. Posner, M. I. (1978). Chronometric explorations of mind. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Posner, M. I. (1980). Orienting of attention. The 7th Sir F. C. Bartlett Lecture. Quarterly Journal of Experimental Psychology, 32, 3–25. Posner, M. I. (1982). Cumulative development of attentional theory. American Psychologist, 32, 53–64. Posner, M. I. (1988). Structures and functions of selective attention. In T. Boll & B. Bryant (Eds.), Master lectures in clinical neuropsychology and brain function: Research, measurement, and practice (pp. 171–202). Washington, DC: American Psychological Association. Posner, M. I. (Ed.) (2004). Cognitive neuroscience of attention. New York: Guilford. Posner, M. I., & Boies, S. J. (1972). Components of attention. Psychological Review, 78, 391–408. Posner, M. I., & Fan, J. (in press). Attention as an organ system. In J. Pomerantz (Ed.), Neurobiology of perception and communication: From synapse to society. The IVth De Lange Conference. Cambridge: Cambridge University Press. Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13, 25–42. Posner, M. I., Petersen, S. E., Fox. P. T., & Raichle, M. E. (1988). Localization of cognitive functions in the human brain. Science, 240, 1627–1631. Posner, M. I., & Raichle, M. E. (1994). Images of mind. New York: Scientific American Library. Posner, M. I., & Raichle, M. E. (Eds.) (1998). The neuroimaging of human brain function. Proceedings of the National Academy of Sciences of the USA, 95, 763–764. Posner, M. I., & Rothbart, M. K. (1998). Attention, self-regulation and consciousness. Philosophical Transactions of the Royal Society of London. B, Biological Sciences, 353, 1915–1927. Posner, M. I., & Rothbart, M. K. (2000). Developing mechanisms of self-regulation. Development and Psychopathology, 12, 427–441. Posner, M. I., Rothbart, M. K., Vizueta, N., Levy, K., Thomas, K. M., & Clarkin, J. (2002). Attentional mechanisms of borderline personality disorder. Proceedings of the National Academy of Sciences of the USA, 99, 16366–16370. Posner, M. I., Rothbart, M. K., Vizueta, N., Thomas, K. M., Levy, K. N., Fossella, J.,

18. Neuropsychology of attention

347

et al. (2003). An approach to the psychobiology of personality disorders. Development and Psychopathology, 15, 1093–1106. Posner, M. I., Walker, J. A., Friedrich, F. J., & Rafal, R. D. (1984). Effects of parietal lobe injury on covert orienting of visual attention. Journal of Neuroscience, 4, 1863–1874. Rainville, P., Duncan, G. H., Price, D. D., Carrier, B., & Bushnell, M. C. (1997). Pain affect encoded in human anterior cingulated but not somatosensory cortex. Science, 277, 968–970. Robertson, I. H., Mattingley, J. B., Rorden, C., & Driver, J. (1998). Phasic alerting of neglect patients overcomes their spatial deficit in visual awareness. Nature, 395, 169–172. Rodier, P. M. (2002). Converging evidence for brain stem injury during autism. Development and Psychopathology, 14, 537–559. Roland, P. E., & Friberg, L. (1985). Localization of cortical areas activation by thinking. Journal of Neurophysiology, 53, 1219–1243. Rothbart, M. K., Ahadi, S. A., & Evans, D. E. (2000). Temperament and personality: Origins and outcomes. Journal of Personality and Social Psychology, 78, 122–135. Rothbart, M. K., Ahadi, S. A., & Hershey, K. (1994). Temperament and social behavior in children. Merrill-Palmer Quarterly, 40, 21–39. Rothbart, M. K., Ellis, L. K., & Posner, M. I. (2004). Temperament and self regulation. In R. F. Baumeister & K. D. Vohs (Eds.), Handbook of self-regulation (pp. 357–370). New York: Guilford Press. Rueda, M. R., Fan, J., McCandliss, B. D., Halparin, J. D., Gruber, D. B., Lercari, L. P., et al. (2004a). Development of attentional networks in childhood. Neuropsychologia, 42, 1029–1040. Rueda, M. R., Posner, M. I., Rothbart, M. K., & Davis-Stober, C. P. (2004b). Development of the time course for processing conflict: An event-related potentials study with 4 year olds and adults. BMC Neuroscience, 5, 39. Rueda, M. R., Rothbart, M. K., McCandlis, B. D., Saccamanno, L., & Posner, M. I. (2005). Training, maturation and genetic influences on the development of executive attention. Proceedings of the National Academy of Sciences of the USA, 102, 14931–14936. Rumbaugh, D. M., & Washburn, D. A. (1995). Attention and memory in relation to learning: A comparative adaptation perspective. In G. R. Lyon and N. A. Krasengor (Eds.), Attention, memory and executive function (pp. 199–219). Baltimore, MD, Brookes. Shavlev, L., Tsal, Y., & Mevorach, C. (2003). Progressive attentional training program: Effective direct intervention for children with ADHD. Proceedings of the Cognitive Neuroscience Society, New York (pp. 55–56). Shulman, G. L., Remington, R., & McLean, J. P. (1979). Moving attention through visual space. Journal of Experimental Psychology: Human Perception and Performance, 5, 522–526. Sternberg, S. (1969). The discovery of processing stages: Extensions of Donders’ method. Acta Psychologica, 30, 276–315. Titchener, E. B. (1909). Experimental psychology of the thought processes. New York: Macmillan. Turken, A. U., & Swick, D. (1999). Response selection in the human anterior cingulate cortex. Nature Neuroscience, 2, 920–924.

348

Posner

Van Veen, V., & Carter, C. S. (2002). The timing of action-monitoring processes in the anterior cingulated cortex. Journal of Cognitive Neuroscience, 14, 593–602. Volpe, B. T., LeDoux, J. E., & Gazzaniga, M. S. (1979). Information processing of visual stimuli in an extinguished visual field. Nature, 282, 1947–1952. Walter, W. G., Cooper, R., Aldridge, V. J., McCallum, W. C., & Winter, A. L. (1964). Contingent negative variation: An electrical sign of sensorimotor association and expectancy in the human brain. Nature, 203, 380–384. Washburn, D. A. (1994). Stroop-like effects for monkeys and humans: Processing speed or strength of association? Journal of Psychological Science, 5, 375–379. Wang, K., Fan, J., Dong, Y., Wang, C., Lee, T. M. C., & Posner, M. I. (2005). Selective impairment of attentional networks of orienting and executive control in schizophrenia. Schizophrenia Research, 78, 235–241. Wurtz, R. H., Goldberg, E., & Robinson, D. L. (1980). Behavioral modulation of visual responses in monkey: Stimulus selection for attention and movement. Progress in Psychobiology and Physiological Psychology, 9, 43–83.

19 Measuring human cognition online by electrophysiological methods The case of selective attention Anna Christina Nobre and Laetitia Silvert The electrical signals of the brain were first measured by an ingenious English physician and lecturer, Richard Caton (1875), using a voltage-sensitive device to move mirrors. He showed that the pattern of shadows cast by this “reflecting galvanometer” attached to the exposed animal brain changes when candlelight stimulation of the eye is interrupted. Some decades later, Hans Berger (1929), a German doctor at Jena, developed a non-invasive method to record the electrical signals of the human brain, which he termed the “electroencephalogram” (EEG). The EEG records the fluctuating changes in voltage over time sensed between an electrode at the scalp and another reference electrode. Berger described its characteristic frequency features, such as the alpha waves (around 8–12 Hz) and beta (around 12–30 Hz) waves, and demonstrated how these could vary according to the functional state and neurological condition of the individual. The view of neuronal activity provided by the EEG is macroscopic and biased. The voltage signals registered at the scalp come mainly from synaptic currents in populations of neurons that are spatially well aligned and whose activity is temporally superimposed (Allison, Wood, & McCarthy, 1986; Creutzfeld & Houchin 1974; Lorente de No, 1947). The logarithmic decay of voltage with distance also biases the recordings to activity in neuronal populations closest to the active electrode. The orientation of the active neuronal tissue relative to the electrodes also influences the polarity and amplitude of the signals. Signals that reach the scalp are thought to reflect synchronized synaptic activity in thousands to millions of neurons (Hämäläinen & Hari, 2002). Excitatory synaptic potentials in the nearby and well-oriented pyramidal cortical cells are thought to be the major players in the signal (Allison et al., 1986; Hämäläinen & Hari, 2002). Specific measures of information processing in neural systems can be extracted from the EEG. Neural activity reliably associated with specific sensory or motor events can be obtained by averaging segments of the EEG that are time-locked to the event of interest. These “event-related potentials” (ERPs) are waveforms with a succession of characteristic peaks and troughs,

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known as components. Components are a source of controlled observable variability (Donchin, Ritter, & McCallum, 1978), which can be defined by their latency, amplitude, voltage topography over the scalp, and functional modulation by experimental variables (Allison et al., 1986; Rugg & Coles, 1995). The relationship they bear to the neural events that generate them can be complex. In some cases, a component may reflect activity in one brain area or circuit during a specific stage of information processing, as in the case of the C1 component that is generated in the primary visual cortex (Clark, Fan, & Hillyard, 1995). However, it is possible that some components reliably measured at the scalp have no direct intracranial component counterparts, but instead result from the summation of multiple temporally overlapping neural processes. Online correlates of perceptual analysis can also be derived by presenting stimuli at a given rate and measuring corresponding changes in the EEG at that same frequency (Regan, 1989). These “steady-state evoked potentials” (SSEPs) provide a continuous readout of the processing of the stimulus in question. By presenting multiple stimuli at different and non-harmonic frequencies, we can track their processing separately. The neural sources of SSEPs are not well characterized and are likely to combine activity from multiple brain areas. The characteristic frequency bands of the EEG, some of which were already described by Berger (1929), are also increasingly recognized to reflect specific aspects of information processing. These oscillatory rhythms arise from the temporal patterns of synchronization within or between populations of neurons. The precise temporal profiles and synchronization of neuronal activity may play a fundamental role in neural signalling and integration, and therefore the ability to chart their modulation may be critical to understanding the neural dynamics behind cognition. Some of the oscillatory rhythms in the EEG are well characterized in terms of neural generators and functional significance, such as the mu rhythm (around 10–20 Hz) in motor cortex. Others continue to be intensively investigated and discussed, such as in the high-frequency gamma band. Analysis of EEG data in the frequency domain can reveal changes in specific bands of neural activity as well as the synchronization of activity at particular frequency bands over different regions of the scalp (see Hari & Salmelin, 1997). The magnetoencephalogram (MEG) records the magnetic fields that accompany the neuronal voltage signals, and is further biased toward neuronal activity in sulci, which are tangentially oriented to the scalp. Magnetic fields are much less attenuated by the scalp than electrical potentials, and therefore MEG has superior spatial resolution to EEG, though all the same constraints regarding spatial and temporal summation still apply. Similar event-related, steady-state, and frequency measures of information processing can be derived from the MEG as from the EEG. MEG requires the use of superconducting technology to measure the weak magnetic fields in the brain, and the resulting associated cost has limited its use (see Hämäläinen & Hari, 2002).

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The EEG and MEG can be sampled from multiple electrodes concurrently, and dense electrode arrays can be used to plot accurate maps of the distribution of voltage or magnetic fields over the scalp. However, identifying the neural generators of EEG- and MEG-related measures remains problematic, since the problem of inferring the configuration of voltage sources in a three-dimensional structure, such as the brain, that projects onto a twodimensional surface, such as the scalp, is mathematically underdetermined and impossible to solve (Helmholtz, 1853). Nevertheless, increasingly effective approaches to localize brain activity are being developed, in which knowledge about brain structure and physiology, as well as convergent findings by methods of higher spatial resolution, is used to constrain the solutions (e.g. Dale & Halgren, 2001; Makeig, Debener, Onton, & Delorme, 2004; Michel, Murray, Lantz, Gonzalez, Spinelli, & Grave, 2004; Phillips, Rugg, & Friston, 2002). Though EEG- and MEG-related measures of neural activity are undisputedly partial and spatially coarse, they hold an important advantage over other non-invasive methods with which to investigate the human brain. They measure neural activity directly and with high temporal precision. This is in contrast with haemodynamic methods, such as positron emission tomography or functional magnetic resonance imaging, that measure brain activity with superior spatial resolution, but only very slowly and indirectly through changes in blood parameters that result from the metabolic aftereffects of neuronal activity (see Huettel, Song, & McCarthy, 2004; Raichle, 1998).

EEG and attention Selective attention can be defined as the set of functions by which neural resources are deployed differentially toward specific attributes of events on the basis of changing expectation, volition, or motivation in order to optimize perception and action. The end products of the selective-attention functions determine the contents of awareness and optimize purposeful action from the limitless possibilities afforded by the environment. The consequences of selective attention can be measured operationally as changes in behavioural or neural responses to a given stimulus, according to changes in its predictability or relevance. EEG-related methods hold several advantages for investigating selective attention. For this purpose, it is imperative to obtain the high temporal resolution necessary to track transient modulations of neural activity along different stages of the information-processing stream. The rich dependent variable provided by EEG is correlated with information processing in real time and can obviate the requirement for overt responses. This enables the assessment of the processing of attended, or relevant, stimuli, as well as of ignored, or irrelevant, stimuli. The methods also allow the individuation of neural responses from different types of stimuli or trials that are intermixed

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and presented at rapid rates. Experimental designs can therefore control for the influences of tonic changes in cognitive state, such as arousal or difficulty (Hillyard, Hink, Schwent, & Picton, 1973). As a consequence, EEG-related methods have played a decisive role in answering the three classic and interrelated questions in selective attention: the unit of selection, the locus of selection, and the mechanism of selection. EEG-related methods have also played an essential role in moulding our current understanding of selective attention as a highly flexible set of functions, able to operate upon several types of representations and to modulate different levels of processing depending on the greatest points of information conflict or load (Nobre, 2004). The units of attentional selection The two earliest rival models proposed that attentional selection operated upon the representations of spatial locations (Broadbent, 1958; Posner, 1980) or upon the representations of objects (Duncan, 1984; Kahneman & Treisman, 1984; Neisser, 1967). This simple dichotomous scenario has been replaced by a more pluralistic view that selective attention can operate on many different types of representation, in a non-mutually exclusive manner. Units that have been proposed to support selective attention also include features and time intervals. Nevertheless, spatial selective attention and objectbased selective attention remain the most extensively investigated. Spatial locations and objects Several behavioural results are consistent with the idea that attentional selection is based on the location of a stimulus. For example, in dichotic listening tasks, directing attention to the location of one stream of information, among competing streams, significantly reduces the amount of knowledge about information at ignored locations (Broadbent, 1958; Cherry, 1953). In spatial orienting tasks, predictive information about the spatial location of stimuli that are relevant to task performance significantly improves the accuracy and reaction times of responses (Posner, 1980). In contrast, object-based theories of selective attention hold that selective attention is directed toward objects following their preattentive extraction from the background stimulation (Duncan, 1984; Neisser, 1967). Supporting evidence comes from demonstrations that there are no additional behavioural costs to responding about constituent features, even if task irrelevant, of the same object, whereas responding about features of different objects does entail significant behavioural costs (Blaser, Pylyshyn, & Holcombe, 2000; Duncan, 1984; Kahneman & Treisman, 1984). Rather than arbitrating between the two competing theories, EEG-related experiments have shown that both spatial and object representations can support attentional selection. Starting in the 1970s, Hillyard and colleagues

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investigated neural modulation by spatial attention by comparing ERPs elicited by identical stimuli within competing streams of information when attended versus ignored. Importantly, these experiments randomized sequences of rapidly presented stimuli under high perceptual load, maximizing perceptual conflict and controlling for overall differences in arousal or task difficulty. Amplitudes of early components of the ERPs (before 200 ms after stimulus onset), reflecting perceptual analysis, were enhanced for attended relative to ignored stimuli in both the auditory (Hillyard et al., 1973) and visual (VanVoorhis & Hillyard, 1977) modalities. Later potentials, reflecting cognitive evaluation and response-related variables, were also enhanced. An experimental industry followed (mainly concentrated on the visual sensory modality), replicating and refining the findings (reviewed in Eimer, 1998; Hillyard & Hansen, 1986; Hillyard & Anllo-Vento, 1998; Mangun, 1995). Spatial attention has been manipulated by instructing subjects to respond to items within only one of multiple competing streams (VanVoorhis & Hillyard, 1977) or by using probabilistic cues that predict the location of relevant stimuli (Eimer, 1994; Mangun & Hillyard 1991). Spatial attention is usually studied by peripheral stimuli, but it can also affect the processing of items within foveal vision (Miniussi, Rao, & Nobre, 2002; Neville & Lawson, 1987). In all cases, the earliest modulations reported are on the P1 and N1 components of the visual ERP, which peak at around 100 and 160 ms, respectively, over lateral posterior electrodes. Modulation of these components has consequences for perception, and can be correlated with behavioural measures of perceptual discriminability (Luck & Hillyard, 1995; Mangun & Hillyard, 1987). Source localization and correlations with complementary structural and functional imaging have shown these components to reflect activity in multiple extrastriate visual areas along both ventral and dorsal visual pathways (Di Russo, Martinez, & Hillyard, 2003; Heinze et al., 1994). Moreover, modulation of the two components can be functionally dissociable (Heinze, Luck, Mangun, & Hillyard, 1990; Hillyard, Munte, & Neville, 1985; Luck, Heinze, Mangun, & Hillyard, 1990), suggesting that spatial attention can affect multiple levels of perceptual analysis with relative independence. Several authors have also investigated the influence of spatial attention on the earliest cortical visual component (C1). This component precedes the P1 and N1, and is related to activation of primary visual cortex situated on the banks of the calcarine sulcus. C1 can easily be missed when using stimuli placed along the horizontal meridian. Indeed, because of the layout of the topographical representation of primary visual cortex along the calcarine, the C1 component reverses polarity when the upper versus lower visual field is stimulated. Nonetheless, careful experiments, using appropriate stimuli to evoke the C1 component have consistently shown no C1 modulation by spatial attention (Clark et al., 1995; Martinez et al., 1999). This finding contrasts with results from haemodynamic brain-imaging studies, which have repeatedly reported modulation of primary visual cortex in spatial attention tasks

354 Nobre and Silvert (e.g. Martinez et al., 1999; Somers, Dale, Seiffert, & Tootell, 1999), and illustrates the requirement for a method with high temporal resolution to investigate the time course of attentional effects. Experiments combining haemodynamic and electrophysiological methods have clarified that though the early activity in primary visual cortex reflected by the C1 component is unaffected, its later activation, which can reflect re-entrant inputs or delayed local computations, is indeed modulated by spatial attention (Di Russo et al., 2003; Martinez, Di Russo, Anllo-Vento, Sereno, Buxton, & Hillyard, 2001; Noesselt et al., 2002). Experiments using single-unit recordings in nonhuman primates have also suggested that attentional modulation in extrastriate regions starts earlier and is more pronounced than in striate cortex (Luck et al., 1997; Reynolds & Chelazzi, 2004; Schroeder, Mehta, & Givre, 1998). Early firing rates in striate cortex are typically unaffected by attentional manipulations, though late modulations (>200 ms) have been reported (e.g. Roelfsema, Lamme, & Spekreijse, 1998), and have been interpreted to reflect modulations due to re-entrant feedback inputs or associative lateral connections within striate cortex. EEG-related experiments have also afforded evidence in favour of an object-based attentional selection. However, this type of selection is difficult to investigate in isolation since object-based and spatial representations are intrinsically bound—objects occupy (or constitute) space (this leads to fascinating but tangential philosophical considerations). For example, spatially specific effects have been observed when attention was selectively directed toward one of two overlapping line-drawing objects presented centrally (Weber, Kramer, & Miller, 1997). Therefore, though many experiments have manipulated selective attention between objects, very few can successfully exclude contributions from spatial attention mechanisms. One particularly ingenious attempt to investigate object-based attention in the absence of spatial factors was made by Valdes Sosa, Bobes, Rodriguez, and Pinilla (1998). They presented sets of red and green dots that moved in opposite circular motion within a central disc area. This generated the percept of two coloured transparent surfaces moving against one another. Occasionally, one surface would change direction and “glide” along a linear path. Participants in the experiment were asked to monitor the movements in one of the two surfaces and detect movements along the cardinal axes. Each dot moved in a probabilistic fashion, negating any strategy based on tracking individual dots spatially. To probe the modulation of information processing, ERPs evoked by the movement of a coloured surface were compared when that surface was relevant to responses (attended) versus irrelevant (ignored). Modulations of the ERPs by attention in this task were pronounced, and were similar to the modulations observed in spatial attention tasks: the amplitudes of the extrastriate P1 and N1 components were enhanced for attended stimuli relative to ignored stimuli. Some may argue that the surface-like stimuli used by Valdes Sosa et al. (1998) may not quite capture “objectness”. However, it may become impossible to rule out spatial features if real objects are used.

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Haemodynamic brain-imaging studies have also supported the ability of selective attention to act upon object-based representations. In tasks using overlapping transparent face and house stimuli, activation of brain areas that respond preferentially to faces versus houses was enhanced when selective attention was directed to a specific feature of the preferred stimulus (O’Craven, Downing, & Kanwisher, 1999). The findings indicated that areas coding object-related information were affected, even when the task did not require any integration of the features within the object. However, the lack of temporal resolution in these experiments do not enable strong conclusions about whether the object-related modulations in activation are instrumental to the selection process, or a consequence of biased feedback after selective processing. The overlapping stimuli used also contained substantial spatial information that could have influenced the selection process. Taken together, findings from spatial and object-based studies show that attention can be directed to either type of representation, and that it is possible to modulate perceptual analysis in the absence of spatial information that dissociates relevant from irrelevant stimuli. However, it may be difficult to define precisely the unit of representation that attention locks onto once directed toward an object or a location. When a location is made relevant, it is still possible that the representations providing the substrates for modulation are defined by the nature of the object. Similarly, when an object is made relevant, the substrates for modulation could be entirely guided by the occupied spatial locations. Features Given the neural organization of visual processing, another obvious target for modulation by selective attention is the level of simple features. Much of the initial perceptual analysis of feature dimensions proceeds in parallel in specialized brain areas (DeYoe & Van Essen, 1988; Felleman & Van Essen, 1991; Zeki, 1993), thus providing a natural neural substrate for the selection of feature dimensions and values. However, object-based attention models argue against features as a natural unit for selection. After all, people interact with objects, and not isolated features. But even so, in many cases, it may be advantageous to consider constituent features within objects to guide action; for example, focusing on colour may be helpful when distinguishing between ripe versus unripe fruit on a tree or, more likely, the supermarket display. Again, one major difficulty is teasing apart feature-specific information from spatial or object-based information. Most of the experiments to date have used arrays with multiple objects and locations, presented simultaneously or sequentially, making it difficult to rule out indirect influences from spatial or object-based attention. When the relevant stimuli in an array are predefined by both spatial location and a specific feature level, ERP modulation based on spatial location precedes that based on feature values

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(Anllo-Vento & Hillyard, 1996; Eimer, 1995, 1997; Hansen & Hillyard, 1983; Hillyard & Hansen, 1986; Hillyard & Munte, 1984; Wijers, Mulder, Okita, Mulder, & Scheffers, 1989). In tasks using rapid, randomized presentation of individual stimuli, the first effect of selective attention is the modulation of P1 and N1 amplitudes as a function of the relevance of stimulus location. Effects based on non-spatial features follow, and usually take the form of a relative negative deflection in the ERP waveform, known as the “selection negativity”, starting at about 160 ms for stimuli with the relevant feature value (Anllo-Vento, 1995; Eimer, 1995, 1997; Hillyard & Hansen, 1986; Hillyard & Munte, 1984). Source localization of feature-selection effects has suggested that they reflect modulation in brain areas specialized for processing the relevant stimulus dimension (Anllo-Vento, Luck, & Hillyard, 1998; Lange, Wijers, Mulder, & Mulder, 1998). During visual search (Treisman & Gelade, 1980), where the location of the relevant target is not known, the first sign of target selection is usually a negative-going deflection at posterior electrodes contralateral to the target location around 180–300 ms, known as the N2pc (Luck & Hillyard, 1994). The N2pc has been linked to the spatial selection of relevant items in the array (Luck, Woodman, & Vogel, 2000), and has been proposed to reflect activity in occipitotemporal cortex (Hopf et al., 2000; Hopf, Vogel, Woodman, Heinze, & Luck, 2002). More recently, earlier markers of selective processing have been reported (Hopf, Boelmans, Schoenfeld, Luck, & Heinze, 2004; Leonards, Palix, Michel, & Ibanez, 2003). When a feature shared by the target stimulus is present in a distractor stimulus, a negative-going modulation occurs over posterior contralateral electrodes before the N2pc. This effect has been associated with the biasing of processing of feature values that are relevant to the task (Hopf et al., 2004). The effect is similar to the modulation of ERPs when participants use a relevant feature that can be at either side of a cueing stimulus to orient spatial attention (Nobre, Sebestyen, & Miniussi, 2000). Single-cell recordings in non-human primates have also shown modulation of activity in neurons coding for a relevant feature value, even when their receptive fields do not overlap with the target stimulus (Motter, 1994; Treue & Martinez-Trujillo, 1999). The findings show that it is possible to process information at the featurespecific level selectively. Furthermore, the attentional modulations based on feature levels differ in nature from those based on spatial locations or objects (Eimer, 1997). However, there is still no conclusive evidence that featurebased selection can occur independently of either object-based or spatialselection mechanisms. It is possible that the ERP (or single-unit) modulations by the task-relevant features are initially triggered by spatial or object-based attention mechanisms. A more convincing demonstration of pure featurebased selective attention would require manipulating the task relevance of different feature dimensions that are co-extensive within single objects (e.g. Fanini, Nobre, & Chelazzi, 2006), and measuring feature-specific neural processing with high temporal resolution.

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Temporal intervals Another major dimension that frames our perception and action is time (see Nobre & O’Reilly, 2004). Though not yet incorporated into major theoretical models of selective attention, a recent line of investigation manipulating the predicted time intervals for relevant task events using probabilistic cues has shown that temporal information can effectively guide selective attention (Griffin & Nobre, 2005; Nobre, 2001). Information provided by temporally informative cues interacts with information inherent in the unidirectional nature of the passage of time itself (Elithorn & Lawrence, 1955) to determine temporal expectations on a dynamic basis. The resulting dynamic function is the probability that a given target will appear given that it has not yet occurred, and is known as the “hazard function”. Target stimuli occurring at an expected compared to unexpected time interval are detected and discriminated more effectively. Behavioural benefits of temporal orienting of attention are robust over changes in specific stimulus configurations and time intervals used, and are of similar magnitude to spatial attention effects (Coull & Nobre, 1998; Griffin, Miniussi, & Nobre, 2001, 2002). Experiments investigating the modulation of neural processing by temporal orienting have reinforced the pluralistic view of units for attentional selection. Despite the similar behavioural consequences of temporal versus spatial expectations, the underlying neural modulations are very different (Griffin et al., 2002; Miniussi, Wilding, Coull, & Nobre, 1999). When cues provide only temporal predictions, visual P1 and N1 components are not modulated in a retinotopically specific way. Instead, pronounced effects occur over later potentials linked to decisions and responses, which differ from modulations observed during spatial attention tasks (Griffin et al., 2002; Miniussi et al., 1999). For example, the latency of the P300 component was diminished for targets appearing at the predicted temporal interval. When compared directly, spatial and temporal orienting effects have been shown to differ in nature despite task parameters being equivalent in all ways except for the information provided by the predictive spatial or temporal cues (Griffin et al., 2002). Temporal orienting tasks used in ERP experiments so far have shown pronounced motor-related modulation and little or no perceptual modulation. However, it is premature to rule out the ability of temporal expectations to modulate perceptual levels of processing under all circumstances. Tasks used to date have required speeded responses, and have involved low levels of perceptual demands or competition of stimuli over time. Enhancing perceptual demands and competition in the temporal domain may bring out earlier effects of temporal orienting of attention. At the behavioural level, temporal orienting has been shown to produce enhancement in the sensitivity of perceptual discriminations (Correa, Lupianez, Milliken, & Tudela, 2004; Lasley & Cohn, 1981; Westheimer & Ley, 1996). Experiments on temporal orienting of attention therefore convincingly

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show that information processing can be modulated along multiple and different stages. Selective attention does not operate at fixed bottleneck points at which resource capacities are limited, as proposed in classic models of selective attention (e.g. Broadbent, 1958; Deutsch & Deutsch, 1963). Instead, top-down signals can act upon multiple levels to bias perceptual analysis or facilitate the selection or execution of relevant responses. The levels of information processing affected depend on the nature of the expectations or instructions and their affordances. Single-unit studies are just beginning to investigate the effects of temporal factors in selective attention (Ghose & Maunsell, 2002; Janssen & Shadlen, 2005). Future studies should prove very useful to investigate different types of modulatory mechanisms also at the cellular level. In addition to any lesson that research on temporal orienting may yield regarding the nature and flexibility of selective attention, its robust behavioural and neural effects warrant a much greater regard for temporal factors in cognitive research in general, and attention-related research in particular. Effects of temporal expectancies may be pervasive in many types of experiments, where they may interact with the experimental factors of interest (Griffin & Nobre, 2005). For example, the use of a fixed or a narrow range of intervals between stimuli is very common and may inadvertently engender temporal expectancies. Status quo and future directions In order to probe the extent of flexibility in the units of attentional selection, it will be interesting to manipulate the task relevance or expectations about additional types of event attributes, especially while also ruling out confounds with spatial or object-based variables. Research to date supports the ability of attention to modulate neural processing related to spatial locations, objects, features, time intervals, and motor responses. Of particular interest will be to test the ability to orient attention to aspects of stimuli that are not specifically tied to perceptual analysis or motor responses. For example, ERPs are being used to investigate the neural consequences of selective attention to semantic categories of words, and to compare the effects of semantic orienting to those of spatial orienting (Cristescu & Nobre, in press). Preliminary results confirm that probabilistic cues predicting the semantic category of word stimuli as well as spatial cues confer behavioural advantages for identifying words, but that the neural mechanisms involved differ significantly. Studies examining the ability of associative, mnemonic, or emotive types of information to serve as the unit of attentional selection would help clarify whether there are any types of stages of information processing that consistently contribute to attentional modulation, or whether attentional modulation is a ubiquitous property across information-processing systems. Once this question is answered, the more difficult question remains regarding whether one or some types of representations are more important to initiate

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attentional selection, which then affects the processing of other types of representations. The investigation into the nature of attentional selection will also benefit from the development of experimental tasks with greater ecological validity. Most selective-attention tasks used routinely fail to capture the complexity of the environments in which selective attention operates in real life. Stimulus arrays are often simple and static, and presented on blank backgrounds. Selective attention is typically manipulated by explicit symbolic cues that predict or provide instructions about the relevant stimulus feature(s). However, in everyday life, expectations derive from memory of previous experience or from the observation of changing perceptual and temporal attributes in dynamic and complex environments. Our laboratory has started designing and implementing more naturalistic tasks for investigating selective attention. We have recently validated the effects of spatial and temporal expectations concerning the reappearance of a transiently occluded object formed as a function of the information inherent in its movement prior to its disappearance behind a barrier (Doherty, Griffin, Rao, & Nobre, 2003). We have also shown the ability of long-term memory of the location of relevant objects to guide the orienting of spatial attention in complex-scene stimuli, of greater ecological validity (Summerfield, Lepsien, Mesulam, & Nobre, 2004). Also ahead is the challenge to understand how multiple units of attentional selection interact. In everyday life, different types of expectations do not occur in isolation. For example, temporal expectations are normally accompanied by expectations about stimulus location and identity. If different sources of relevant information can interact at the neural level, this could lead to synergistic modulatory mechanisms. In this case, studying specific types of attention in isolation may lead to a deceptive picture of how information processing is tuned dynamically during experience. The locus of attentional selection From the earliest research on attention, one of the most fundamental questions has been the locus of attentional selection. Does the attentional selection occur at an early stage of processing (early selection) or at a late stage (late selection)? The early selection account posits that attention operates prior to stimulus identification (e.g. Broadbent, 1958; Treisman, 1985). Selective attention is alleged to be based on spatial location or on preattentively available properties such as colour or orientation, whose processing can occur in parallel over the visual field, and selective attention is alleged to control which stimuli have access to the mechanism that completes identification. In this view, unattended stimuli are not processed beyond their initial physical attributes. In contrast, the late selection account (e.g. Deutsch & Deutsch, 1963; Duncan, 1980) holds that attentional selection is based not only on lowerlevel properties, but also on object identities that have been processed in

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parallel. In other words, selection is assumed to occur only after categorization and semantic analysis of all incoming material have occurred. The question as to whether attention gates perceptual or post-perceptual processing cannot be definitively resolved through the analysis of behavioural data, since they usually reflect the sum of both early and late stages of stimulus analysis, yielding ambiguous evidence. However, due to their temporal resolution, electrophysiological techniques such as ERP can be used to measure the influence of the attentional processes on different stages of information processing directly, providing unique evidence in the early/late selection debate. Evidence for early selection The locus of selection can be assessed by simply comparing the ERP waveforms elicited by an attended stimulus and by a physically identical unattended stimulus. The time point at which the two waveforms start to diverge indicates how soon after stimulus onset selection first occurs (more precisely, this time point provides an upper bound on the initial effect of attention, since there might be earlier effects that are not manifest in the ERP waveforms). With this method, a large body of ERP research in the visual modality has consistently found evidence for early selection (see Luck et al., 2000, for a review). As mentioned above, in many spatial attention studies, the ERPs elicited by attended and unattended stimulus begin to differ in the latency range of the P1 component, indicating that the processing of these stimuli can be modulated by attention at or before this time. However, the effect of attentional selection is often to attenuate the response to unattended stimuli rather than filtering it out completely. Therefore, the possibility of early attentional modulation does not necessarily mean that irrelevant sensory inputs are not processed at all. A second way to address the early/late selection question is to assess whether unattended stimuli can be discriminated on the basis of high-level features, such as their task relevance. Evidence for early selection has been obtained by Hillyard and Munte (1984), who found that there is no difference between ERPs elicited by target and non-target stimuli appearing at unattended locations in the N2 range, while differential treatment between these two types of stimuli was seen at the attended locations. However, Drysdale et al. (1995, 1998) have reported that both reaction time and the lateralized N2 are affected by the target status of unattended letters, the N2 showing a greater negative deflection to target than non-target letters at both attended and unattended locations. An even more straightforward approach to the early/late selection question is to investigate directly whether semantic processing can occur for unattended stimuli. In this framework, the N400 component of the ERPs has received a great deal of interest. The N400 is a large, broadly distributed, centroparietal negative component peaking approximately 300–600 ms after the onset of a

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stimulus and reflecting the degree of mismatch between a word and a previously established semantic context (Kutas & Hillyard, 1980). The N400 potential is attenuated if the word is repeated or preceded by a semantically related word (Bentin, McCarthy, & Wood, 1985). Since the meaning of the word must be extracted before it can be matched to the semantic context, a large N400 for an incongruent word can be considered as evidence that the word has been processed to a point at which some elements of its meaning are available. Investigations of N400 modulations for verbal material presented at unattended locations seem to indicate that semantic processing is at least partially gated by spatial attention. For example, in McCarthy and Nobre’s study (1993), subjects had to focus attention on alternate visual fields to perform a category-detection task, and pairs of semantically related and repeated words were embedded in the word lists presented to the attended and unattended visual fields. For the attended words, the N400 component was smaller for semantically primed or repeated words. However, the N400 was not elicited by unattended words (see Otten, Rugg, & Doyle, 1993, for similar results when attentional selection is based on the colour of the words). Comparable data have also been obtained by Bentin, Kutas, and Hillyard (1995) in a dichotic listening task. They showed that the N400 elicited by attended words was modulated by semantic priming between successive words, whereas the N400 elicited by unattended words was insensitive to semantic manipulation (see also Okita & Jibu, 1998, for converging evidence). However, in some cases, experiments have found evidence for residual lexical or semantic analysis of unattended words (Ruz, Worden, Tudela, & McCandliss, 2005; Yamagata, Yamaguchi, & Kobayashi, 2000). Taken together, the data are consistent with an early locus of spatial attentional selection, but with a probabilistic or relative mechanism for attenuating irrelevant stimuli. Evidence for late selection Evidence regarding semantic processing of unattended words mainly comes from the attentional blink literature. The attentional blink is typically observed when subjects have to detect two target stimuli (T1 and T2) among distractors under rapid serial visual presentation conditions (up to 20 items per second at the same spatial location; Raymond et al., 1992). When T1 is correctly identified, the detection of the T2 is substantially impaired if it appears 200–500 ms after T1. This effect, replicated in hundreds of papers (see Shapiro, Arnell, & Raymond, 1997), is thought to reflect the demands of attending to and identifying the first target. Lack of awareness of the second target can be explained as a transitory deficit in the allocation of limited attentional resources over time rather than over space (e.g. Chun & Potter, 1995; Shapiro, Raymond, & Arnell, 1994; Vogel, Luck, & Shapiro, 1998; Ward, Duncan, & Shapiro, 1996).

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Several ERP components have been compared to determine the stage at which the processing is suppressed during the attentional blink. A recurrent finding in these studies is that missed words within the attentional blink do not elicit the P300 component of the ERP (Dell’Acqua, Jolicoeur, Pesciarelli, Job, & Palomba, 2003; Kranczioch, Debener, & Engel, 2003; Rolke, Heil, Streb, & Hennighausen, 2001; Vogel et al., 1998; Vogel & Luck, 2002). Despite the different interpretations of the functional significance of the P300, there is a general consensus that this component is an electrophysiological correlate of processes associated with working memory (Donchin & Coles, 1988; Johnson, 1986; Kok, 2001). Thus, the fact that blinked stimuli are not associated with a P300 component is consistent with the proposal that the attentional blink operates before or during the process of forming a stable representation of T2 in working memory. However, Vogel et al. (1998, experiment 1) have demonstrated that the impairment in the detection of T2 during the attentional blink is not accompanied by a suppression of the P1 and N1 components elicited by probe flashes appearing concurrently with T2. This finding suggests that the attentional blink is not the result of the suppression of sensory processing. But can the semantic meaning of the blinked words be processed? This question has been directly addressed by Vogel et al. (1998; see also Luck et al., 1996; Rolke et al., 2001). In Vogel et al.’s study (1998, experiment 2), T1 was a digit target and T2 a word target, presented among strings of letters. Immediately before each stream, a context word was presented, and the subjects were asked to report whether the T2 word was semantically related to the context word. The N400 effect (that is, a larger component for unrelated words than for related words) appeared to be unaffected by the fact that T2 was perceived or missed due to the attentional blink. Compatible data have been obtained by Rolke et al. (2001) with a different procedure. They have shown that detected as well as missed words presented in the attentional blink interval similarly affect the N400 evoked by a probe word presented approximately 600 ms later in the stream of visual stimulations. Taken together, these ERP studies suggest that stimuli presented during the attentional blink can be analysed perceptually and processed up to a semantic level, providing arguments in favour of a late locus of attentional selection in this phenomenon. There is no evidence, however, that this semantic processing is as complete as the processing of attended stimuli. Status quo and future directions The ERP data described above provide good evidence that attentional selection can occur at different stages of visual processing under different conditions. Interestingly, early selection seems to occur mainly for stimuli presented at unattended locations and late selection for unattended stimuli presented at fixation (see also, for example, Kiefer, 2002, for evidence for N400 modulation by masked words). But this is obviously an oversimplification of the story. Due to the wide heterogeneity of procedures and stimuli

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used, a more cautious conclusion would be that selection may operate at different levels depending on the requirements of task, and one of the critical factors could be the stimulus load. For example, Lavie (2001) has proposed that irrelevant information is processed as long as it falls within the capacity limit of perception, but fails to be processed as soon as it exceeds this limit. As a consequence, conditions of high load would lead to early selection whereas conditions of low load would lead to late selection. And indeed, why should the perception of an unattended stimulus be suppressed if the perceptual system is not overloaded? According to Luck and Hillyard (1999), the same logic could be applied to any cognitive subsystem (e.g. early sensory analysis, object recognition, working memory, response selection): selective processing would occur in a given subsystem when that subsystem has to deal with the competing demands of multiple stimuli or tasks (see also Kahneman & Treisman, 1984). Nevertheless, strict early or late views of attentional selection definitely appear to be unsatisfactory: both early and late selection mechanisms have to be considered in a complete account of selective attention. Moreover, with EEG-related methods, researchers are not restricted to coarsely defined cognitive subsystems (that is, early versus late). EEG-related methods applied to appropriate experimental designs make it possible to investigate more specifically how attention can operate at better-defined processing stages (Luck et al., 2000), which should allow furthering the debate concerning the loci of attentional selection. The mechanisms of attentional selection The different measures derived from the EEG are complex and macroscopic in nature. Nevertheless, they can also help reveal the neural mechanisms for modulating information processing. As already stated, ERP studies have shown that neural processing of several different types of representations can be modulated by selective attention, from the level of simple features to the level of semantic analysis and integration. The spotlight of attention The notion of attention as a single spatial spotlight (Broadbent, 1982; Posner, Snyder, & Davidson, 1980) is clearly outdated. Some kind of spatial spotlight mechanism may exist, but studies using visual steady-state evoked potentials have shown that the areas of space that are highlighted can be discontinuous (Muller, Malinowski, Gruber, & Hillyard, 2003), and take on complex shapes (Muller & Hübner, 2002). For example, it is possible to direct attention to a ring of items while ignoring the central location (Muller & Hübner, 2002). Beyond spotlights, there seem to be object boosters, feature lenses, temporal wobblers, and others.

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Gain control Attention directed to spatial locations or objects leads to enhancement of the amplitude of ERP components (see Hillyard, Vogel, & Luck, 1998; Luck et al., 2000). These canonical findings have been interpreted to reflect a gaincontrol mechanism for selective attention, in which attended stimuli receive more intensive analysis than ignored stimuli (Hillyard, Mangun, Woldorff, & Luck, 1995; Hillyard et al., 1998). Enhanced selection negativities for relevant features have been interpreted in a similar way (Hillyard & Anllo-Vento, 1998). Dissociation in the modulation of the various perceptual components and in selection negativities across tasks has indicated that gain-control attention mechanisms can operate at multiple levels with relative independence. The exact cellular bases of these effects are difficult to determine. There is no a priori way of differentiating between enhanced processing of the attended stimuli and diminished processing of the ignored stimuli in the ERP modulations. Findings from single-unit recordings in non-human primates have shown enhanced neuronal firing associated with attended items, such as in posterior parietal cortex (Robinson, Goldberg, & Stanton, 1978; see Colby & Goldberg, 1999) and in frontal eye fields (Goldberg & Bushnell, 1981; Thompson, Bichot, & Schall, 1997), as well as filtering of information related to ignored items, such as in ventral visual areas (Chelazzi, Miller, Duncan, & Desimone, 1993; Moran & Desimone, 1985; Reynolds, Chelazzi, & Desimone, 1999). Effects on the latency of perceptual processing are not typically found, though they have been observed during peripheral cueing tasks (Anllo-Vento, 1995) and when attended stimuli in a spatial sustained-attention task were compared with passively viewed stimuli, using visual steady-state evoked potentials (Di Russo & Spinelli, 2002). In contrast, latency modulation of later, post-perceptual processes occurs reliably in studies manipulating selective attention to time intervals, and has been proposed to reflect more sharply tuned response selection and execution (Doherty et al., 2003; Griffin et al., 2002; Miniussi et al., 1999). It may be premature to rule out mechanisms based on latency modulation of perceptual analysis completely. To date, selective-attention tasks have not introduced much conflict or competition for stimulus discrimination in the temporal domain. Rapid stimulus presentation has been used, but usually with only one stream of stimuli in order to study the temporal limitations in information processing, such as in the attentional blink (Raymond, Shapiro, & Arnell, 1992). It would be interesting to place multiple rapid streams of information in competition in order to study selective attention under larger time pressure. It is possible that under such circumstances additional mechanisms involving latency modulation of stimulus analysis would contribute to biasing stimulus analysis according to behavioural goals. Single-cell recordings associating the degree of attentional modulation in neuronal firing with specific temporal hazard function (Ghose & Maunsell, 2002; Janssen & Shadlen, 2005) support the possibility of

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biasing information processing through latency-related mechanisms as well as through overall gain-control mechanisms. Anticipatory activity Adjustments to top-down attentional biasing are triggered by changes in predictions or instructions. Behavioural experiments of visual spatial orienting indicate that voluntary shifts of spatial attention occur within a few hundred milliseconds, with cue–target intervals as short as 200 ms (Posner, 1980). Activity in attentional control systems has been investigated by measuring the neural responses to informative or instructive cueing stimuli. Most studies have investigated brain activity related to orienting spatial attention, and have shown a sequence of lateralized potentials that are thought to reflect activity in the parietal-frontal system that controls spatial orienting of attention. The earliest ERP marker of spatial orienting is a negative deflection over the posterior scalp contralateral to the side toward which attention is oriented, occurring within 200 ms (Harter, Anllo-Vento, & Wood, 1989; Yamaguchi, Tsuchiya, & Kobayashi, 1994). This effect can be observed even when an identical stimulus is used to orient attention to different visual fields (Nobre et al., 2000). Because of the types of visual cueing stimuli used, it is not clear whether the effect reflects spatial selection of the relevant portions within the cueing stimulus (Van Velzen & Eimer, 2003) or activity related to spatial orienting, or both. The next lateralized component has a frontal distribution starting around 300 ms, and can be linked more securely to spatial orienting. It is triggered by spatial orienting cues regardless of the sensory modality of the cue or target stimulus (Eimer & VanVelzen, 2002). Starting around 500 ms after the cue and before the presentation of visual stimuli, there is also a sustained positive modulation over posterior electrodes contralateral to the predicted side. This “late directed attention positivity” has been interpreted to reflect changes in tonic activity of neurons whose receptive fields code relevant spatial locations (e.g. Eimer & VanVelzen, 2002; Hopf & Mangun, 2000). Single-unit recordings have likewise shown that firing rates in extrastriate neurons with receptive fields in task-relevant locations are enhanced by spatial (Luck et al., 1997) as well as object-based (Chelazzi et al., 1993) attention. In line with the plurality of attentional modulatory mechanisms, neural activity specific to attentional control can also vary significantly depending on the predicted stimulus attribute. When cues predict the time intervals for ensuing targets, preparatory activity during the cue–target interval consists primarily of the enhancement of broad negative components distributed over midline scalp regions, starting around 300 ms (Miniussi et al., 1999). This modulation is thought to include the contingent negative variation component with similar distribution and time course (Walter, Cooper, Aldridge, & McCallum, 1964), which has been linked to expectancies and motor preparation (e.g. Macar, Vidal, & Casini, 1999).

366 Nobre and Silvert Synchronization Analysis of the EEG in the frequency domain has begun to provide another perspective on the neural mechanisms of attentional modulation and control. Attended stimuli induce significantly more oscillatory activity in the highfrequency (30–80 Hz) gamma band than do ignored stimuli. Increases in gamma-band responses occur in the context of spatial attention in multiple modalities as well as across sensory modalities (Gruber, Muller, Keil, & Elbert, 1999; Muller, Gruber, & Keil, 2000; Pantev, Makeig, Hoke, Galambos, Hampson, & Gallen, 1991; Sokolov, Lutzenberger, Pavlova, Preissl, Braun, & Birbaumer, 1999; Tiitinen, Sinkkonen, Reinikainen, Alho, Lavikainen, & Naatanen, 1993) as well as feature-based attention to colour (Muller & Keil, 2004). In the colour-attention task, modulation of induced gamma activity occurred early during perceptual analysis, in the temporal window corresponding to feature-specific selection-negativity modulation in the averaged ERP waveforms (Muller & Keil, 2004). In addition to the increase in the highfrequency gamma-band response, a later decrease in low-frequency alphaband response was observed (Muller & Keil, 2004). Similar increases in gamma activity and decreases in alpha activity induced by attended relative to ignored stimuli in a spatial attention task have also been observed with single-unit and field-potential recordings in non-human primates (Fries, Reynolds, Rorie, & Desimone, 2001). Overall, induced gamma-band activity represents regional synchronization of neuronal activity at high frequencies, which serves to boost the effect of the synchronized cells upon efferent regions. Desynchronization of activity in the alpha-band range has also been hypothesized to enhance postsynaptic transmission, by diminishing spikefrequency adaptation (Fries et al., 2001). However, the precise theoretical implications, as well as the cellular bases for gamma-band and alpha-band activity, remain unresolved (Engel & Singer, 2001; Gruber et al., 2001; Herrmann, Lenz, Junge, Busch, & Maess, 2004; Pulvermuller, Keil, & Elbert, 1999; Tallon-Baudry & Bertrand, 1999). Modulation of frequency-based activity in the EEG also occurs during anticipatory phases of selective attention tasks (Bastiaansen & Brunia, 2001; Foxe, Simpson, & Ahlfors, 1998; Fu, Fan, Chen, & Zhuo, 2001; Worden, Foxe, Wang, & Simpson, 2000). Differential degrees of synchronization in cortical networks according to anticipated stimulus attributes could therefore influence the degree of information processing engendered by sensory stimulation (see Muller & Gruber, 2001; Muller & Keil, 2004). For example, with enhanced preparatory high-frequency synchronization, stimulation by the expected attribute(s) would strengthen the neural synchronization, whereas stimulation by irrelevant or ignored attributes would result in decoupling and a decrease in the power of synchronized activity. Alternatively, desynchronization of low-frequency activity related to expected relevant attributes or synchronization of low-frequency activity to ignored distracting attributes could facilitate overall processing of relevant attributes (Bastiaansen & Brunia,

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2001; Worden et al., 2000). Experiments comparing conditions requiring attention to be directed internally, to perform mental-imagery tasks, versus externally, to perform sensory-intake tasks, have supported a role for synchronized, low-frequency alpha activity to inhibit irrelevant sensory information (Cooper, Croft, Dominey, Burgess, & Gruzelier, 2003). Status quo and future directions So far, our understanding of the mechanisms of attentional selection is only formative. We have some important pieces to the puzzle, but no conclusive overall view. EEG-related experiments have contributed significantly to the pieces so far, and are likely to continue to play an important role. For now we know that attentional selection operates on multiple types of units and at multiple stages of the processing hierarchy. Gain control can be achieved both by enhancement and by filtering of information within receptive fields. Modulation of tonic firing rates contributes to attentional selection between receptive fields. Differential synchronization of activity in cells whose receptive-field properties code relevant versus irrelevant stimulus attributes is also likely to play a key role. Furthermore, the timing of these selection functions is likely to vary depending on temporal expectations. Ultimately, complete understanding of the attentional selection mechanisms may require investigations at the cellular and subcellular levels, but there is still ample scope for experiments using non-invasive EEG-related measures. Future experiments analysing data in both the frequency and time domains will help chart the relationship between frequency-related changes in the EEG and amplitude-related changes in the ERPs. Continued emphasis on analysis of frequency-related data will also uncover any general principles regarding the relationship between frequency-related activity and different types of selective attention modulation and control. For example, it will be very interesting to test whether synchronization in the gamma band is a general mechanism for integrating top-down expectations with bottom-up analysis of the sensory input, as proposed recently (Herrmann et al., 2004). Indeed, understanding this confluence between top-down biases relating to intentions or expectations and the bottom-up analysis of sensory inputs is one of the most interesting challenges ahead. One fruitful approach will be to combine the high temporal resolution of EEG-related methods with the noninvasive interference method of transcranial magnetic stimulation to investigate the interplay between attentional control areas and their targeted sites for modulation (Taylor, Mandon, Freiwald, & Kreiter, 2005). Investigating the roles of neurotransmitter systems in dynamic attentional control functions will also be very important (e.g. Yamaguchi & Kobayashi, 1998). Probing this crucial interface of selective attention may prompt us to dig into issues that are even more basic than the classic questions in attentional research we have addressed in this chapter. For example, we may wish to question even the prevailing assumption that there are sets of neural systems

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and mechanisms that differentiate between attentional control (source of attention) and attentional modulation (site of attention). Instead, the brain areas that trigger modulation of information processing as well as the mechanisms that shape neuronal signalling within task-relevant circuits may depend on the nature of the changing expectations, motivations, and task goals (Nobre, 2004).

References Allison, T., Wood, C. C., & McCarthy, G. (1986). The central nervous system. In M. G. H. Coles, E. Donchin, & S. W. Porges (Eds.), Psychophysiology: Systems, processes, and applications (pp. 5–25). New York: Guilford Press. Anllo-Vento, L. (1995). Shifting attention in visual space: The effects of peripheral cueing on brain cortical potentials. International Journal of Neuroscience, 80, 353–570. Anllo-Vento, L., & Hillyard, S. A. (1996). Selective attention to the color and direction of moving stimuli: Electrophysiological correlates of hierarchical feature selection. Perception and Psychophysics, 58, 191–206. Anllo-Vento, L., Luck, S. J., & Hillyard, S. A. (1998). Spatio-temporal dynamics of attention to color: Evidence from human electrophysiology. Human Brain Mapping, 6, 216–238. Bastiaansen, M. C., & Brunia, C. H. (2001). Anticipatory attention: An event-related desynchronization approach. International Journal of Psychophysiology, 43, 91–107. Bentin, S., Kutas, M., & Hillyard, S. A. (1995). Semantic processing and memory for attended and unattended words in dichotic listening: Behavioral and electrophysiological evidence. Journal of Experimental Psychology: Human Perception and Performance, 21, 54–67. Bentin, S., McCarthy, G., & Wood, C. C. (1985). Event-related potentials, lexical decision and semantic priming. Electroencephalography and Clinical Neurophysiology, 60, 343–355. Berger, H. (1929). Über das Elektrenkephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten, 87, 527–570. Blaser, E., Pylyshyn, Z. W., & Holcombe, A. O. (2000). Tracking an object through feature space. Nature, 408, 196–199. Broadbent, D. E. (1958). Perception and communication. London: Pergamon Press. Broadbent, D. E. (1982). Task combination and selective intake of information. Acta Psychologica, 50, 253–290. Caton, R. (1875). The electric currents of the brain. British Medical Journal, 2, 278. Chelazzi, L., Miller, E. K., Duncan, J., & Desimone, R. (1993). A neural basis for visual search in inferior temporal cortex. Nature, 363, 345–347. Cherry, E. C. (1953). Some experiments on the recognition of speech, with one and with two ears. Journal of the Acoustical Society of America, 25, 975–979. Chun, M. M., & Potter, M. C. (1995). A two-stage model for multiple target detection in rapid serial visual presentation. Journal of Experimental Psychology: Human Perception and Performance, 21, 109–127. Clark, V. P., Fan, S., & Hillyard, S. A. (1995). Identification of early visually evoked potential generators by retinotopic and topographic analyses. Human Brain Mapping, 2, 170–187.

19. Measuring human cognition electrophysiologically

369

Colby, C. L., & Goldberg, M. E. (1999). Space and attention in parietal cortex. Annual Review of Neuroscience, 22, 319–349. Cooper, N. R., Croft, R. J., Dominey, S. J., Burgess, A. P., & Gruzelier, J. H. (2003). Paradox lost? Exploring the role of alpha oscillations during externally vs. internally directed attention and the implications for idling and inhibition hypotheses. International Journal of Psychophysiology, 47, 65–74. Correa, A., Lupianez, J., Milliken, B., & Tudela, P. (2004). Endogenous temporal orienting of attention in detection and discrimination tasks. Perception and Psychophysics, 66, 264–278. Coull, J. T., & Nobre, A. C. (1998). Where and when to pay attention: The neural systems for directing attention to spatial locations and to time intervals as revealed by both PET and fMRI. Journal of Neuroscience, 18, 7426–7435. Creutzfeld, O., & Houchin, J. (1974). Neuronal basis of EEG-waves. Handbook of electroencephalography and clinical neurophysiology (vol. 2, Part C, pp. 2C-5–2C55). Amsterdam: Elsevier. Cristescu, T. G., & Nobre, A. C. (in press). Differential modulation of word recognition by semantic and spatial orienting of attention. Journal of Cognitive Neuroscience. Dale, A. M., & Halgren, E. (2001). Spatiotemporal mapping of brain activity by integration of multiple imaging modalities. Current Opinion in Neurobiology, 11, 202–208. Dale, A. M., Liu, A. K., Fischl, B. R., Buckner, R. L., Belliveau, J. W., Lewine, J. D., & Halgren, E. (2000). Dynamic statistical parametric mapping: Combining fMRI and MEG for high-resolution imaging of cortical activity. Neuron, 26, 55–67. Dell’Acqua, R., Jolicoeur, P., Pesciarelli, F., Job, R., & Palomba, D. (2003). Electrophysiological evidence of visual encoding deficits in a cross-modal attentional blink paradigm. Psychophysiology, 40, 629–639. Deutsch, J. A., & Deutsch, D. (1963). Attention: Some theoretical considerations. Psychological Review, 70, 80–90. DeYoe, E. A., & Van Essen, D. C. (1988). Concurrent processing streams in monkey visual cortex. Trends in Neuroscience, 11, 219–226. Di Russo, F., Martinez, A., & Hillyard, S. A. (2003). Source analysis of event-related cortical activity during visuo-spatial attention. Cerebral Cortex, 13, 486–499. Di Russo, F., & Spinelli, D. (2002). Effects of sustained, voluntary attention on amplitude and latency of steady-state visual evoked potential: A costs and benefits analysis. Clinical Neurophysiology, 113, 1771–1777. Doherty, J., Griffin, I. C., Rao, A., & Nobre, A. C. (2003). Spatial versus temporal expectancies derived from object movement differentially modulate stimulus processing. 33rd Annual Meeting of the Society for Neuroscience. New Orleans, LA, USA. Donchin, E., & Coles, M. G. H. (1988). Is the P300 component a manifestation of context updating? Behavioral and Brain Sciences, 11, 357–374. Donchin, E., Ritter, W., & McCallum, W. C. (1978). Cognitive psychophysiology: The endogenous components of the ERP. In E. Callaway, P. Tueting, & S. H. Koslow (Eds.), Brain event-related potentials in man (pp. 349–411). New York: Academic Press. Drysdale, K. A., Finlay, D. C., & Fulham, W. R. (1995). An event-related potential examination of attended and unattended stimuli in visual selection using bilateral stimulus presentation. Biological Psychology, 39, 115–129.

370

Nobre and Silvert

Drysdale, K. A., Fulham, W. R., & Finlay, D. C. (1998). Event-related potential response to attended and unattended locations in an interference task. Biological Psychology, 48, 1–19. Duncan, J. (1980). The locus of interference in the perception of simultaneous stimuli. Psychological Review, 87, 272–300. Duncan, J. (1984). Selective attention and the organization of visual information. Journal of Experimental Psychology: General, 113, 501–517. Eimer, M. (1994). “Sensory gating” as a mechanism for visuospatial orienting: Electrophysiological evidence from trial-by-trial cuing experiments. Perception and Psychophysics, 55, 667–675. Eimer, M. (1995). ERP correlates of transient attention shifts to color and location. Biological Psychology, 41, 167–182. Eimer, M. (1997). An event-related potential (ERP) study of transient and sustained visual attention to color and form. Biological Psychology, 44, 143–160. Eimer, M. (1998). Mechanisms of visuospatial attention: Evidence from event-related potentials. Visual Cognition, 5, 257–286. Eimer, M., & Schroger, E. (1995). The location of preceding stimuli affects selective processing in a sustained attention situation. Electroencephalography and Clinical Neurophysiology, 94, 115–128. Eimer, M., & Schroger, E. (1998). ERP effects of intermodal attention and crossmodal links in spatial attention. Psychophysiology, 35, 313–327. Eimer, M., & Van Velzen, J. (2002). Crossmodal links in spatial attention are mediated by supramodal control processes: Evidence from event-related potentials. Psychophysiology, 39, 437–349. Elithorn, A., & Lawrence, C. (1955). Central inhibition—some refractory observations. Quarterly Journal of Experimental Psychology, 11, 211–220. Engel, A. K., & Singer, W. (2001). Temporal binding and the neural correlates of sensory awareness. Trends in Cognitive Sciences, 5, 16–25. Fanini, A., Nobre, A. C., & Chelazzi, L. (2006). Selecting and ignoring the component features of a visual object: A negative priming paradigm. Visual Cognition, 14, 584–618. Felleman, D. J., & Van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1, 1–47. Foxe, J. J., Simpson, G. V., & Ahlfors, S. P. (1998). Parieto-occipital approximately 10 Hz activity reflects anticipatory state of visual attention mechanisms. Neuroreport, 9, 3929–3933. Fries, P., Reynolds, J. H., Rorie, A. E., & Desimone, R. (2001). Modulation of oscillatory neuronal synchronization by selective visual attention. Science, 291, 1560–1563. Fu, S., Fan, S., Chen, L., & Zhuo, Y. (2001). The attentional effects of peripheral cueing as revealed by two event-related potential studies. Clinical Neurophysiology, 112, 172–185. Ghose, G. M., & Maunsell, J. H. (2002). Attentional modulation in visual cortex depends on task timing. Nature, 419, 616–620. Goldberg, M. E., & Bushnell, M. C. (1981). Behavioral enhancement of visual responses in monkey cerebral cortex. II. Modulation in frontal eye fields specifically related to saccades. Journal of Neurophysiology, 46, 773–787. Griffin, I. C., Miniussi, C., & Nobre, A. C. (2001). Orienting attention in time. Frontiers in Bioscience, 6, D660–D671.

19. Measuring human cognition electrophysiologically

371

Griffin, I. C., Miniussi, C., & Nobre, A. C. (2002). Multiple mechanisms of selective attention: Differential modulation of stimulus processing by attention to space or time. Neuropsychologia, 40, 2325–2340. Griffin, I. C., & Nobre, A. C. (2005). Temporal orienting of attention. In L. Itti, G. Rees, & J. Tsotsos (Eds.), Neurobiology of attention (pp. 257–263). San Diego, CA: Elsevier. Gruber, T., Keil, A., & Muller, M. M. (2001). Modulation of induced gamma band responses and phase synchrony in a paired associate learning task in the human EEG. Neuroscience Letters, 316, 29–32. Gruber, T., Muller, M. M., Keil, A., & Elbert, T. (1999). Selective visual-spatial attention alters induced gamma band responses in the human EEG. Clinical Neurophysiology, 110, 2074–2085. Hämäläinen, M., & Hari, R. (2002). Magnetoencephalographic characterization of dynamic brain activation: Basic principles and methods of data collection and source analysis. In A. W. Toga & J. C. Mazziotta (Eds.), Brain mapping: The methods (2nd ed., pp. 227–253). San Diego, CA: Academic Press. Hansen, J. C., & Hillyard, S. A. (1983). Selective attention to multidimensional auditory stimuli. Journal of Experimental Psychology: Human Perception and Performance, 9, 1–19. Hari, R., & Salmelin, R. (1997). Human cortical oscillations: A neuromagnetic view through the skull. Trends in Neuroscience, 20, 44–49. Harter, M. R., Anllo-Vento, L., & Wood, F. B. (1989). Event-related potentials, spatial orienting, and reading disabilities. Psychophysiology, 26, 404–421. Heinze, H. J., Luck, S. J., Mangun, G. R., & Hillyard, S. A. (1990). Visual eventrelated potentials index focused attention within bilateral stimulus arrays. I. Evidence for early selection. Electroencephalography and Clinical Neurophysiology, 75, 511–527. Heinze, H. J., Mangun, G. R., Burchert, W., Hinrichs, H., Scholz, M., Munte, T. F., et al. (1994). Combined spatial and temporal imaging of brain activity during visual selective attention in humans. Nature, 372, 543–546. Helmholtz, H. L. F. (1853). Ueber einige Gesetze der Vertheilung elektrischer Ströme in körperlichen Leitern mit Anwendung auf die thierisch-elektrischen Versuche. Annalen der Physik und Chemie, 89, 211–233; 353–377. Herrmann, C. S., Lenz, D., Junge, S., Busch, N. A., & Maess, B. (2004). Memorymatches evoke human gamma-responses. BMC Neuroscience, 5, 13. Hillyard, S. A., & Anllo-Vento, L. (1998). Event-related brain potentials in the study of visual selective attention. Proceedings of the National Academy of Sciences of the USA, 95, 781–787. Hillyard, S. A., & Hansen, J. C. (1986). Attention and electrophysiological approaches. In M. G. H. Coles, E. Donchin, & S. W. Porges (Eds.), Psychophysiology: Systems, processes, and applications (pp. 227–245). New York: Guilford Press. Hillyard, S. A., Hink, R. F., Schwent, V. L., & Picton, T. W. (1973). Electrical signs of selective attention in the human brain. Science, 182, 177–180. Hillyard, S. A., Mangun, G. R., Woldorff, M. G., & Luck, S. J. (1995). Neural systems mediating selective attention. In M. S. Gazzaniga (Ed.), The cognitive neurosciences (pp. 665–681). Cambridge, MA: MIT Press. Hillyard, S. A., & Munte, T. F. (1984). Selective attention to color and location: An analysis with event-related brain potentials. Perception and Psychophysics, 36, 185–198.

372

Nobre and Silvert

Hillyard, S. A., Munte, T. F., & Neville, H. J. (1985). Visual-spatial attention, orienting and brain physiology. In M. I. Posner & O. S. Marin (Eds.), Mechanisms of attention: Attention and performance (pp. 63–84). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Hillyard, S. A., Vogel, E. K., & Luck, S. J. (1998). Sensory gain control (amplification) as a mechanism of selective attention: Electrophysiological and neuroimaging evidence. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 353(1373), 1257–1270. Hopf, J. M., Boelmans, K., Schoenfeld, M. A., Luck, S. J., & Heinze, H. J. (2004). Attention to features precedes attention to locations in visual search: Evidence from electromagnetic brain responses in humans. Journal of Neuroscience, 24, 1822–1832. Hopf, J. M., Luck, S. J., Girelli, M., Hagner, T., Mangun, G. R., Scheich, H., & Heinze, H. J. (2000). Neural sources of focused attention in visual search. Cerebral Cortex, 10, 1233–1241. Hopf, J. M., & Mangun, G. R. (2000). Shifting visual attention in space: An electrophysiological analysis using high spatial resolution mapping. Clinical Neurophysiology, 111, 1241–1257. Hopf, J. M., Vogel, E., Woodman, G., Heinze, H. J., & Luck, S. J. (2002). Localizing visual discrimination processes in time and space. Journal of Neurophysiology, 88, 2088–2095. Huettel, S. A., Song, A. W., & McCarthy, G. (2004). Functional magnetic resonance imaging. Sunderland, MA: Sinauer. Janssen, P., & Shadlen, M. N. (2005). A representation of the hazard rate of elapsed time in macaque area LIP. Nature Neuroscience, 8, 234–241. Johnson, R., Jr. (1986). A triarchic model of P300 amplitude. Psychophysiology, 23, 367–384. Kahneman, D., & Treisman, A. (1984). Changing views of attention and automaticity. In R. Parasuraman & R. Davies (Eds.), Varieties of attention (pp. 29–61). New York: Academic Press. Kiefer, M. (2002). The N400 is modulated by unconsciously perceived masked words: Further evidence for an automatic spreading activation account of N400 priming effects. Cognitive Brain Research, 13, 27–39. Kok, A. (2001). On the utility of P3 amplitude as a measure of processing capacity. Psychophysiology, 38, 557–577. Kranczioch, C., Debener, S., & Engel, A. K. (2003). Event-related potential correlates of the attentional blink phenomenon. Cognitive Brain Research, 17, 177–187. Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruity. Science, 207, 203–205. Lange, J. J., Wijers, A. A., Mulder, L. J., & Mulder, G. (1998). Color selection and location selection in ERPs: Differences, similarities and “neural specificity”. Biological Psychology, 48, 153–182. Lasley, D. J., & Cohn, T. (1981). Detection of a luminance increment: Effect of temporal uncertainty. Journal of the Optical Society of America, 71, 845–850. Lavie, N. (2001). Capacity limits in selective attention: Behavioral evidence and implications for neural activity. In J. Braun, C. Koch, & J. L. Davis (Eds.), Visual attention and cortical circuits (pp. 49–68). Cambridge, MA: MIT Press. Leonards, U., Palix, J., Michel, C., & Ibanez, V. (2003). Comparison of early cortical networks in efficient and inefficient visual search: An event-related potential study. Journal of Cognitive Neuroscience, 15, 1039–1051.

19. Measuring human cognition electrophysiologically

373

Lorente de No, R. (1947). A study of nerve physiology. Studies from the Rockefeller Institute, 132, 384–477. Luck, S. J., Chelazzi, L., Hillyard, S. A., & Desimone, R. (1997). Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex. Journal of Neurophysiology, 77, 24–42. Luck, S. J., Heinze, H. J., Mangun, G. R., & Hillyard, S. A. (1990). Visual eventrelated potentials index focused attention within bilateral stimulus arrays. II. Functional dissociation of P1 and N1 components. Electroencephalography and Clinical Neurophysiology, 75, 528–542. Luck, S. J., & Hillyard, S. A. (1994). Spatial filtering during visual search: Evidence from human electrophysiology. Journal of Experimental Psychology: Human Perception and Performance, 20, 1000–1014. Luck, S. J., & Hillyard, S. A. (1995). The role of attention in feature detection and conjunction discrimination: An electrophysiological analysis. International Journal of Neuroscience, 80, 281–297. Luck, S. J., & Hillyard, S. A. (1999). The operation of selective attention at multiple stages of processing: Evidence from human and monkey electrophysiology. In M. S. Gazzaniga (Ed.), The new cognitive neurosciences (2nd ed., pp. 687–700). Cambridge, MA: MIT Press. Luck, S. J., Vogel, E. K., & Shapiro, K. L. (1996). Word meanings can be accessed but not reported during the attentional blink. Nature, 383, 616–618. Luck, S. J., Woodman, G. F., & Vogel, E. K. (2000). Event-related potential studies of attention. Trends in Cognitive Sciences, 4, 432–441. Macar, F., Vidal, F., & Casini, L. (1999). The supplementary motor area in motor and sensory timing: Evidence from slow brain potential changes. Experimental Brain Research, 125, 271–280. Makeig, S., Debener, S., Onton, J., & Delorme, A. (2004). Mining event-related brain dynamics. Trends in Cognitive Sciences, 8, 204–210. Mangun, G. R. (1995). Neural mechanisms of visual selective attention. Psychophysiology, 32, 4–18. Mangun, G. R., & Hillyard, S. A. (1987). The spatial allocation of visual attention as indexed by event-related brain potentials. Human Factors, 29, 195–211. Mangun, G. R., & Hillyard, S. A. (1991). Modulations of sensory-evoked brain potentials indicate changes in perceptual processing during visual-spatial priming. Journal of Experimental Psychology: Human Perception and Performance, 17, 1057–1074. Martinez, A., Anllo-Vento, L., Sereno, M. I., Frank, L. R., Buxton, R. B., Dubowitz, D. J., et al. (1999). Involvement of striate and extrastriate visual cortical areas in spatial attention. Nature Neuroscience, 2, 364–369. Martinez, A., Di Russo, F., Anllo-Vento, L., Sereno, M. I., Buxton, R. B., & Hillyard, S. A. (2001). Putting spatial attention on the map: Timing and localization of stimulus selection processes in striate and extrastriate visual areas. Vision Research, 41, 1437–1457. McCarthy, G., & Nobre, A. C. (1993). Modulation of semantic processing by spatial selective attention. Electroencephalography and Clinical Neurophysiology, 88, 210–219. Michel, C. M., Murray, M. M., Lantz, G., Gonzalez, S., Spinelli, L., & Grave, D. P. (2004). EEG source imaging. Clinical Neurophysiology, 115, 2195–2222. Miniussi, C., Rao, A., & Nobre, A. C. (2002). Watching where you look: Modulation

374

Nobre and Silvert

of visual processing of foveal stimuli by spatial attention. Neuropsychologia, 40, 2448–2460. Miniussi, C., Wilding, E. L., Coull, J. T., & Nobre, A. C. (1999). Orienting attention in time. Modulation of brain potentials. Brain, 122, 1507–1518. Moran, J., & Desimone, R. (1985). Selective attention gates visual processing in the extrastriate cortex. Science, 229, 782–784. Motter, B. C. (1994). Neural correlates of attentive selection for color or luminance in extrastriate area V4. Journal of Neuroscience, 14, 2178–2189. Muller, M. M., & Gruber, T. (2001). Induced gamma-band responses in the human EEG are related to attentional information processing. Visual Cognition, 8, 579–592. Muller, M. M., Gruber, T., & Keil, A. (2000). Modulation of induced gamma band activity in the human EEG by attention and visual information processing. International Journal of Psychophysiology, 38, 283–299. Muller, M. M., & Hübner, R. (2002). Can the spotlight of attention be shaped like a doughnut? Evidence from steady-state visual evoked potentials. Psychological Science, 13, 119–124. Muller, M. M., & Keil, A. (2004). Neuronal synchronization and selective color processing in the human brain. Journal of Cognitive Neuroscience, 16, 503–522. Muller, M. M., Malinowski, P., Gruber, T., & Hillyard, S. A. (2003). Sustained division of the attentional spotlight. Nature, 424, 309–312. Neisser, U. (1967). Cognitive psychology. New York: Appleton-Century Crofts. Neville, H. J., & Lawson, D. (1987). Attention to central and peripheral visual space in a movement detection task: An event-related potential and behavioral study. I. Normal hearing adults. Brain Research, 405, 253–267. Nobre, A. C. (2001). Orienting attention to instants in time. Neuropsychologia, 39, 1317–1328. Nobre, A. C. (2004). Probing the flexibility of attentional orienting in the human brain. In M. I. Posner (Ed.), Cognitive neuroscience of attention (pp. 157–179). New York: Guilford Press. Nobre, A. C., Coull, J. T., Maquet, P., Frith, C. D., Vandenberghe, R., & Mesulam, M. M. (2004). Orienting attention to locations in perceptual versus mental representations. Journal of Cognitive Neuroscience, 16, 363–373. Nobre, A. C., & O’Reilly, J. (2004). Time is of the essence. Trends in Cognitive Sciences, 8, 387–389. Nobre, A. C., Sebestyen, G. N., & Miniussi, C. (2000). The dynamics of shifting visuospatial attention revealed by event-related potentials. Neuropsychologia, 38, 964–974. Noesselt, T., Hillyard, S. A., Woldorff, M. G., Schoenfeld, A., Hagner, T., Jancke, L., et al. (2002). Delayed striate cortical activation during spatial attention. Neuron, 35, 575–587. O’Craven, K. M., Downing, P. E., & Kanwisher, N. (1999). fMRI evidence for objects as the units of attentional selection. Nature, 401, 584–587. Okita, T., & Jibu, T. (1998). Selective attention and N400 attenuation with spoken word repetition. Psychophysiology, 35, 260–271. Otten, L. J., Rugg, M. D., & Doyle, M. C. (1993). Modulation of event-related potentials by word repetition: The role of visual selective attention. Psychophysiology, 30, 559–571. Pantev, C., Makeig, S., Hoke, M., Galambos, R., Hampson, S., & Gallen, C. (1991).

19. Measuring human cognition electrophysiologically

375

Human auditory evoked gamma-band magnetic fields. Proceedings of the National Academy of Sciences of the USA, 88, 8996–9000. Phillips, C., Rugg, M. D., & Friston, K. J. (2002). Anatomically informed basis functions for EEG source localization: Combining functional and anatomical constraints. NeuroImage, 16, 678–695. Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3–25. Posner, M. I., Snyder, C. R., & Davidson, B. J. (1980). Attention and the detection of signals. Journal of Experimental Psychology, 109, 160–174. Pulvermuller, F., Keil, A., & Elbert, T. (1999). High-frequency brain activity: Perception or active memory? Trends in Cognitive Sciences, 3, 250–252. Raichle, M. E. (1998). Behind the scenes of functional brain imaging: A historical and physiological perspective. Proceedings of the National Academy of Sciences of the USA, 95, 765–767. Raymond, J. E., Shapiro, K. L., & Arnell, K. M. (1992). Temporary suppression of visual processing in an RSVP task: An attentional blink? Journal of Experimental Psychology: Human Perception and Performance, 18, 849–860. Regan, D. (1989). Human brain electrophysiology: Evoked potentials and evoked magnetic fields in science and medicine. New York: Elsevier. Reynolds, J. H., & Chelazzi, L. (2004). Attentional modulation of visual processing. Annual Review of Neuroscience, 27, 611–647. Reynolds, J. H., Chelazzi, L., & Desimone, R. (1999). Competitive mechanisms subserve attention in macaque areas V2 and V4. Journal of Neuroscience, 19, 1736–1753. Robinson, D. L., Goldberg, M. E., & Stanton, G. B. (1978). Parietal association cortex in the primate: Sensory mechanisms and behavioral modulations. Journal of Neurophysiology, 41, 910–932. Roelfsema, P. R., Lamme, V. A. F., & Spekreijse, H. (1998). Object-based attention in the primary visual cortex of the macaque monkey. Nature, 395, 376–381. Rolke, B., Heil, M., Streb, J., & Hennighausen, E. (2001). Missed prime words within the attentional blink evoke an N400 semantic priming effect. Psychophysiology, 38, 165–174. Rugg, M. D., & Coles, M. G. H. (1995). Electrophysiology of mind. Oxford: Oxford University Press. Ruz, M., Worden, M. S., Tudela, P., & McCandliss, B. D. (2005). Inattentional amnesia to words in a high attentional load task. Journal of Cognitive Neuroscience, 17, 768–776. Schroeder, C. E., Mehta, A. D., & Givre, S. J. (1998). A spatiotemporal profile of visual system activation revealed by current source density analysis in the awake macaque. Cerebral Cortex, 8, 575–592. Shapiro, K. L., Arnell, K. M., & Raymond, J. E. (1997). The attentional blink. Trends in Cognitive Sciences, 1, 291–296. Shapiro, K. L., Raymond, J. E., & Arnell, K. M. (1994). Attention to visual pattern information produces the attentional blink in rapid serial visual presentation. Journal of Experimental Psychology: Human Perception and Performance, 20, 357–371. Sokolov, A., Lutzenberger, W., Pavlova, M., Preissl, H., Braun, C., & Birbaumer, N. (1999). Gamma-band MEG activity to coherent motion depends on task-driven attention. Neuroreport, 10, 1997–2000.

376

Nobre and Silvert

Somers, D. C., Dale, A. M., Seiffert, A. E., & Tootell, R. B. (1999). Functional MRI reveals spatially specific attentional modulation in human primary visual cortex. Proceedings of the National Academy of Sciences of the USA, 96, 1663– 1668. Summerfield, J., Lepsien, J., Mesulam, M. M., & Nobre, A. C. (2004). Orienting attention based on long-term memory experience. 34th Annual Meeting of the Society for Neuroscience. San Diego, CA, USA. Tallon-Baudry, C., & Bertrand, O. (1999). Oscillatory gamma activity in humans and its role in object representation. Trends in Cognitive Sciences, 3, 151–162. Taylor, K., Mandon, S., Freiwald, W. A., & Kreiter, A. K. (2005). Coherent oscillatory activity in monkey area V4 predicts successful allocation of attention. Cerebral Cortex, 15, 1424–1437. Thompson, K. G., Bichot, N. P., & Schall, J. D. (1997). Dissociation of visual discrimination from saccade programming in macaque frontal eye field. Journal of Neurophysiology, 77, 1046–1050. Tiitinen, H., Sinkkonen, J., Reinikainen, K., Alho, K., Lavikainen, J., & Naatanen, R. (1993). Selective attention enhances the auditory 40-Hz transient response in humans. Nature, 364, 59–60. Treisman, A. (1985). Preattentive processing in vision. Computer Vision, Graphics and Image Processing, 31, 156–177. Treisman, A. M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12, 97–136. Treue, S., & Martinez-Trujillo, J. C. (1999). Feature-based attention influences motion processing gain in macaque visual cortex. Nature, 399, 575–579. Valdes-Sosa, M., Bobes, M. A., Rodriguez, V., & Pinilla, T. (1998). Switching attention without shifting the spotlight: Object-based attentional modulation of brain potentials. Journal of Cognitive Neuroscience, 10, 137–151. van Velzen, J., & Eimer, M. (2003). Early posterior ERP components do not reflect the control of attentional shifts toward expected peripheral events. Psychophysiology, 40, 827–831. Van Voorhis, S. T., & Hillyard, S. A. (1977). Visual evoked potentials and selective attention to points in space. Perception and Psychophysics, 22, 54–62. Vogel, E. K., & Luck, S. J. (2002). Delayed working memory consolidation during the attentional blink. Psychonomic Bulletin and Review, 9, 739–743. Vogel, E. K., Luck, S. J., & Shapiro, K. L. (1998). Electrophysiological evidence for a postperceptual locus of suppression during the attentional blink. Journal of Experimental Psychology: Human Perception and Performance, 24, 1656–1674. Walter, W. G., Cooper, R., Aldridge, V. J., & McCallum, W. C., & Winter, A. L. (1964). Contingent negative variation: An electric sign of sensorimotor association and expectancy in the human brain. Nature, 203, 380–384. Ward, R., Duncan, J., & Shapiro, K. L. (1996). The slow time-course of visual attention. Cognitive Psychology, 30, 79–109. Weber, T. A., Kramer, A. F., & Miller, G. A. (1997). Selective processing of superimposed objects: An electrophysiological analysis of object-based attentional selection. Biological Psychology, 45, 159–182. Westheimer, G., & Ley, E. (1996). Temporal uncertainty effects on orientation discrimination and stereoscopic thresholds. Journal of the Optical Society of America A (Optics, Image Science, and Vision), 13, 884–886. Wijers, A. A., Mulder, G., Okita, T., Mulder, L. J., & Scheffers, M. K. (1989). Attention

19. Measuring human cognition electrophysiologically

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to color: An analysis of selection, controlled search, and motor activation, using event-related potentials. Psychophysiology, 26, 89–109. Worden, M. S., Foxe, J. J., Wang, N., & Simpson, G. V. (2000). Anticipatory biasing of visuospatial attention indexed by retinotopically specific alpha-band electroencephalography increases over occipital cortex. Journal of Neuroscience, 20, RC63. Yamagata, S., Yamaguchi, S., & Kobayashi, S. (2000). Event-related evoked potential study of repetition priming to attended and unattended words. Cognitive Brain Research, 10, 167–171. Yamaguchi, S., & Kobayashi, S. (1998). Contributions of the dopaminergic system to voluntary and automatic orienting of visuospatial attention. Journal of Neuroscience, 18, 1869–1878. Yamaguchi, S., Tsuchiya, H., & Kobayashi, S. (1994). Electroencephalographic activity associated with shifts of visuospatial attention. Brain, 117, 553–562. Zeki, S. (1993). The visual association cortex. Current Opinion in Neurobiology, 3, 155–159.

20 The frontal lobe Executive, emotional, and neurological functions Paul J. Eslinger

The frontal lobe is among the most complex and intriguing regions of the brain from basic and clinical neuroscience perspectives. It is composed of primary motor and premotor cortices that are crucial for action knowledge and control, and also the prefrontal cortex that has been described as both an enigma and the organ of civilization. While other cortical regions are defined by their dedicated roles in sensory-perceptual and cognitive aspects of visual, spatial, auditory, language, somatosensory, and memory processing, the prefrontal cortex harbors a challenging array of executive control, goal-directed, emotional, and social functions that are essential for the self-regulation of thought, action, and emotions over time and place. The latter processes provide the foundation not only for human development but also for adaptive functioning in unpredictably changing and demanding environments. Frontal lobe syndromes constitute some of the most perplexing effects of brain damage and can be deceptively disabling. For these reasons, the frontal lobe and more specifically the prefrontal cortex encompass areas of intense research and clinical evaluation in children, adults, and older persons (Grafman, 1995a; Levin, Eisenberg, & Benton, 1991; Miller & Cummings, 2007; Stuss & Knight, 2002). This chapter is designed to highlight and integrate both clinical and organizational aspects of frontal lobe functions, drawing on clinical neuropsychological analysis of frontal lesions as well as more recent functional brain-imaging methods. Emphasis is placed on the region of the prefrontal cortex because of its vital role in many aspects of human behavior and adaptation. As a student and colleague of Professor Arthur Benton over 25 years, I heard him speak endearingly of Professor Vignolo, to whom this volume is dedicated. Hence, preparation of the chapter held special significance in honoring this leading figure in Italian neuropsychology. The early history of the frontal lobes and behavior has been traced by Benton (1991b) to seminal experiments and observations that continue to intrigue neuroscientists. Perhaps the most vivid clues to frontal lobe functions were presented in the report by Harlow (1848, 1868) of the case of Phineas Gage, who suffered brain injury from passage of an iron bar through the head while working with a demolition crew constructing railroad tracks in Vermont. The iron shot up through Gage’s cheek and exited the vertex of the

380 Eslinger head, causing a localized bilateral prefrontal lesion. Harlow described that as a result of this brain lesion, Gage was no longer himself, undergoing marked change in his emotions, personality, and the adaptive control of his behavior. In modern terms, Gage would be described as having suffered from a frontal lobe syndrome with profound and persistent change in his personality and executive functions (Stuss & Benson, 1986; Stuss, Gow, & Hetherington, 1992; Tranel et al., 1994). These devastating impairments occurred in relative isolation from other neurological deficits, as motor and premotor regions of the frontal lobe were not damaged. Gage subsequently led an aimless and erratic life, marked by disorganization, impulsivity, and social-emotional difficulties. Gage was permanently disabled by his prefrontal cortex damage, despite the fact that his speech and language, perceptual, sensory-motor abilities, and memory were all clinically considered to be within normal limits. This unusual behavioral profile was characterized by marked inconsistencies between apparently intact cognitive abilities and impaired adaptive functioning in everyday situations. Contemporary studies have confirmed that this clinical profile is associated primarily with localized damage to the prefrontal cortex, particularly in the orbital and ventromedial prefrontal region (Dimitrov, Phipps, Zahn, & Grafman, 1999; Eslinger & Damasio, 1985). Figure 20.1 shows the brain scan of such a patient. This learned and successful gentleman in his thirties developed a tumor affecting the orbital region of the prefrontal cortex that was skillfully removed by the neurosurgeon. His medical recovery was excellent, and IQ measurement after surgery placed him at the 99th percentile for his age, in the very superior range. Not only was his measured intelligence exceptional, but many observations and measurements of his memory and learning, speech and language, perception, and motor functions were entirely normal. He appeared gregarious and interacted with others socially. His emotions were stable and well regulated. Yet, this man was unable to return to his prior work in accounting and to resume his family and community relationships, despite these remarkable cognitive abilities. He was unable to organize himself sufficiently to arrive at work on time, to decide where he would like to dine, to organize and complete his work, and to follow through on almost anything he planned. His executive functions became very limited, particularly in utilizing changing information, responding appropriately to the competing demands and responsibilities he previously managed well, and modifying his approach to daily goals when his initial actions were inadequate. His family reported that he had undergone a change in personality and was no longer reliable. This clinical profile helps characterize several aspects of executive functions. That is, the executive functions are necessary for independent and adaptive functioning in nonroutine and changing environments, yet are not correlated with general measured intelligence. Rather, the executive functions utilize intellectual capacities for the purposes of achieving goals, planning, prioritizing, keeping important information in mind to guide actions, moving from one action to another throughout the day, reflecting upon progress, and implementing modifications to meet goals and responsibilities. While

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Figure 20.1 Brain scan of patient EVR demonstrating localized prefrontal cortical damage that was associated with profound change in organization of goal-directed behavior despite preserved cognitive abilities.

general intellect might be considered the what of cognition (that is, crystallized knowledge or what we know), the executive functions encompass the how and why of cognition and behavior. Although converging evidence suggests that the executive functions are subserved by networks of cortical and subcortical structures, damage to the prefrontal cortex causes the most profound disruptions of executive functions, often leading to permanent impairments and disability from a variety of diseases (Bogousslavsky, 1994; Eslinger & Chakara, 2004). These clinical presentations can be diverse and encompass fascinating and important observations about the workings of the human brain, neural plasticity, and the capacity for recovery of functions, as described below. The following section presents an overview of the anatomic and functional organization of the

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frontal lobe, focusing principally on the prefrontal cortex, executive functions, and prominent frontal lobe syndromes.

Anatomic organization and neural networks The cytoarchitecture and connectional anatomy of the frontal lobe have been investigated in postmortem specimens and with diverse methods in the nonhuman primate (eg. Barbas, 1995; Barbas & Pandya, 1989, 1991; Mesulam & Mufson, 1982; Nauta, 1971; Porrino, Crane, & Goldman-Rakic, 1981; Price, Carmichael, & Drevets, 1996). The frontal lobe comprises the primary motor cortex, premotor cortex, and prefrontal cortex (Figure 20.2).

Figure 20.2 Major regions of the frontal lobe including the primary motor, premotor, and prefrontal cortex. The prefrontal cortex is further divided into lateral, mesial, and ventral regions with distinctive anatomic and functional characteristics. (This figure is published in color at www.psypress.com/ brainscans-etc/)

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The prominent anatomic landmarks, cytoarchitectonic areas, and affiliation with neural systems of these regions are summarized in Table 20.1. The primary motor cortex, designated as Brodmann’s area 4, is located just anterior to the central sulcus and spans the inferior to superior extent of the lateral frontal lobe. In this region, there is a homuncular organization of Table 20.1 Anatomic features of specialized frontal lobe regions Regions

Prominent anatomic landmarks

Brodmann’s cytoarchitectonic areas

Neural systems

Primary motor and premotor cortices

Central sulcus/ precentral gyrus Broca’s area (left)

4, 6 (lateral) 44, 45

Motor Premotor

Dorsolateral prefrontal cortex

Frontal pole Inferior Middle Superior

8, 9, 10, 11,

Prefrontal

Superior mesial

Central sulcus/ precentral gyrus Supplementary motor area Anterior cingulate gyrus

4 (mesial), 6 (mesial) 24

Motor Premotor Limbic

Inferior mesial

Subcallosal gyrus Mesial gyrus rectus

25, 32, 14, 12

Paralimbic Prefrontal

Lateral frontal region

Mesial frontal region

Ventral frontal region Basal forebrain

Septal nuclei Precommissural fornix Nucleus accumbens Substantia innominata Diagonal band of Broca

Orbital

Gyrus rectus Olfactory tracts Orbital gyri Medial Middle Lateral

Deep white matter

Periventricular (rostral, lateral, inferior, superior to frontal horns)

Limbic

10, 11, 13, 14, 47

Paralimbic Prefrontal

Frontal-striatal Frontal-thalamic Frontal-limbic Frontal-cortical pathways

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motor representation, with mediation of oral, speech, and facial motor abilities in the most inferior lateral aspects; of the upper extremities in the mid-lateral region; and of the lower extremities, trunk, bowel, and bladder in the superior medial region. The primary motor cortex receives most of its input from the premotor region and has output pathways to the basal ganglia, brainstem, and spinal cord via descending pyramidal and extrapyramidal system tracts. Anterior to the primary motor cortex is the premotor cortex, including the supplementary motor area, which are important motor association areas that are involved with motor learning, memory, preparedness, and activation. The premotor cortex is also extensively interconnected with the cerebellum. Moreover, the primary motor and premotor cortices are networked extensively with the basal ganglia, thalamus, and cerebellum through a number of specific pathways and relays that permit physiological modulation. An important extension of the premotor cortex is Broca’s area (Brodmann’s areas 44 and 45), which provides a crucial neural substrate for speech and language processing. The prefrontal cortex is the region located anterior to the motor and premotor areas. It can be divided grossly into lateral, mesial, and ventral (or orbital) prefrontal regions that are characterized by specific types of cytoarchitecture and patterns of connectional anatomy with other cortical and subcortical structures. The lateral, mesial, and ventral prefrontal regions are differentiated both anatomically and functionally, as described below. The lateral prefrontal cortex (Figure 20.2) has multiple gyri and cytoarchitectonic areas that have anatomic and physiological characteristics of association cortex, extending forward to the frontal poles. It is composed of a six-layered cortex that has rich cortico-cortical connections with sensoryspecific association areas, particularly visual, auditory, and somatosensory association cortices, as well as with multimodal association areas in the inferior parietal lobe and the lateral and medial temporal lobe. It can be considered among the most complex convergence areas in the brain for cortical and subcortical connections (Barbas & Pandya, 1989, 1991). Parallel frontal-subcortical pathways interconnect this region with the basal ganglia, thalamus, hypothalamus, amygdala, and hippocampus (Alexander, Crutcher, & DeLong, 1990). Thus, dorsolateral and ventrolateral prefrontal cortices are in a position to receive and reciprocate highly processed information that is multimodal in nature. In cell recording and functional brainimaging studies, this region becomes activated by a variety of cognitive processing tasks, most notably working memory, decision-making, and problem-solving (Casey et al., 1995; Fuster, 1991; Goldman-Rakic, 1987; Jonides et al., 1993; Petrides, Alivisatos, Meyer, & Evans, 1993). Through reciprocal connections, the dorsolateral and ventrolateral prefrontal cortices can influence cortical sensory-motor areas in mediating processes such as attentional shifting, delayed responding, relational reasoning, and modulation of emotions. The mesial prefrontal region comprises cortical areas that arc around the

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anterior half of the corpus callosum on the interhemispheric surface. The superior mesial portion extends from the supplementary motor area (or mesial premotor cortex) to the frontal poles. These mesial extensions of dorsolateral prefrontal areas are still being investigated and may have different functional significance in self-referential, self–other representation, theory of mind, self-regulatory, and emotional processing domains. The anterior cingulate gyrus is located between the mesial prefrontal cortex and the corpus callosum. As a paralimbic cortical region, it is interconnected with other limbic system structures and particularly the orbital frontal and insula cortex. It appears to have diverse roles in viscerosomatic processing (as in pain), as well as attention, conflict resolution, and emotional tone. The inferior mesial prefrontal region is located rostral to the genu of the corpus callosum and encompasses the subcallosal gyrus as well as posterior ventromedial cortical areas implicated in emotion (including depression and obsessive-compulsive disorder) and viscerosomatic/psychosomatic modulation (Drevets et al., 1997; Price, 1999). The ventral prefrontal region is identified by the characteristic olfactory bulbs and tracts that traverse this cortical undersurface of the rostral brain from the olfactory nerve, ascending through the cribiform plate, to reach the posterior-medial edge of the orbital frontal cortex. This ventromedial region comprises not only olfactory areas but also paralimbic cortex and the basal forebrain region. The latter encompasses a cluster of nuclei and pathways that comprise the nucleus basalis (which is important in acetylcholine production), the septal nucleus (a limbic-related structure interconnected with the hippocampus), the nucleus accumbens (which has been linked to reward mechanisms), and multiple pathways. The paralimbic aspects of the posterior ventromedial region have been implicated in visceral-autonomic regulation affecting heart rate, respiration, gastric motility, and other effector systems (see Eslinger, 1999, for review). In contrast, the large expanse of granular orbital prefrontal cortex has characteristics of association cortex, being interconnected with multimodal association areas, insula, cingulate, and important subcortical areas in the dorsomedial thalamus, hypothalamus, and amygdala. This cortical region provides a pivotal neural substrate for emotion-related processing, including learning (such as positive and negative reinforcement contingencies), perception (emotional faces and voices), and inhibitory control of behavior (Price 1999; Rolls, 1990). Because of the importance of emotion and inhibition for interpersonal processing, it is thought that many aspects of social cognition and social emotion involve orbital frontal mediation.

Clinical frontal syndromes There are a variety of diseases that affect the frontal lobe. Expression of clinical deficits varies depending upon the particular disease, the momentum of its onset (as in slow insidious versus sudden), disease progression variables,

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and individual differences in cerebral organization and neural compensatory processes. Common diseases include: • • • • • • • • •

stroke in the anterior cerebral artery distribution and anterior branches of the middle cerebral artery, including hemorrhagic and ischemic stroke aneurysm and arteriorvenous malformations of the anterior, anterior communicating, and middle cerebral arteries head trauma with contusions, hemorrhage, and axonal shearing hydrocephalus, including normal pressure hydrocephalus tumors of various pathophysiology multiple sclerosis frontotemporal dementia herpes simplex encephalitis neurodevelopmental disorders, including attention deficit hyperactivity disorder, fragile X, fetal alcohol syndrome, and high-functioning autism.

Lateral frontal syndromes As described in Table 20.2, damage to the primary motor and premotor cortices can result in a variety of clinical impairments, including hemiparesis (typically in a contralateral extremity), dysarthria, apraxia, motor impersistence, and nonfluent aphasia. Apraxias are motor disorders that are not related to specific deficiencies in strength or sensation, but rather are instrumental impairments in motor movements, sequencing, and actions due to other cognitive-motor processing deficits. Nonfluent aphasia, most prominently described as Broca’s aphasia, is associated with damage to the left inferior lateral region (Brodmann’s areas 44 and 45). Patients with Broca’s aphasia typically present with nonfluent speech that is effortful and agrammatic, with relatively preserved comprehension of language. Damage to the homologous area in the right premotor region has been associated with aprosodia or the loss of the emotional intonation of speech. There are prominent clinical syndromes associated with damage to the dorsolateral and ventrolateral prefrontal cortex. Some of these are specific to damage in the left or right hemispheres, but the most profound result from bilateral damage due to tumor, traumatic brain injury, and other causes. Such patients are often described as perseverative, repeating responses and actions over and over without self-monitoring and self-correction of their behavior, and are unable to manage adaptive behavioral responses (Sirigu, Zalla, Pillon, Grafman, Agid, & Dubois, 1995). Disinhibition, disorganization in thinking and behavior, rigid thinking, limited working memory, attentional impairment, and stimulus boundedness are common features. The last refers to disproportionate attention to the immediate environment, inability to disengage from surrounding stimuli, and withholding of responding until appropriate time and place. For example, such patients lose the ability to regulate their behavior from mental models and goals, and become preoccupied with the

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Table 20.2 Prominent impairments associated with damage to specific frontal lobe regions Region

Clinical impairments

Lateral frontal region Primary motor and premotor cortices

Hemiparesis Dysarthria Aprosodia

Apraxia (oral and limb kinetic) Motor impersistence Nonfluent aphasia (left)

Dorsolateral prefrontal cortices

Disorganized thinking and behavior Perseveration Poor planning Impulsive responding Stimulus boundedness Poor self-regulation

Impaired working memory Cognitive rigidity Intentional disorders Inattention Lack of empathy Conjugate eye deviation

Right

Left

Left hemispatial neglect Poor spatial cognition

Transcortical motor aphasia

Superior mesial cortices

Akinesia/bradykinesia Apathy Apraxia Grasp reflex Intentional disorders

Mutism Utilization behavior Alien hand, anarchic hands Altered self-regulation Callosal disconnection signs

Inferior mesial cortices

Disinhibition Utilization behavior Altered self-regulation

Lack of motivation Altered emotions processing

Basal forebrain

Amnesia Reduced motivation

Confabulations Delusions (e.g. Capgras syndrome, reduplicative paramnesia)

Orbital cortices

Personality change Poor social judgment Lack of goal-directed behavior Environmental dependency

Impulsive actions Reduced empathy Altered self-regulation

Deep white-matter region

Personality change Reduced emotions

Poor empathy Irritability

Mesial frontal region

Ventral frontal region

immediate circumstances they encounter. All of these clinical signs and symptoms contribute to what is described as poor self-regulation or the inability to organize and manage one’s behavior in socially appropriate and goal-directed ways across time and in diverse environments and interpersonal

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situations. Focal damage to the right dorsolateral prefrontal region has been associated with left hemispatial neglect or inattention to the left side of extrapersonal space. Poor spatial cognition in the form of impaired perception, problem solving, attention, and memory may also be observed. An example of such a lesion is presented in Figure 20.3. The clock drawing of this 7-year-old child with focal right dorsolateral prefrontal damage is shown in Figure 20.4. The right dorsolateral prefrontal cortex has also been linked specifically to spatial working memory, discourse, pragmatic and figurative aspects of language (including affective expression), and memory retrieval, as well as spatial reasoning, fluency, and problem solving (Bottini et al., 1994; Eslinger, Biddle, & Grattan, 1997; Marlowe, 1992; Tulving et al., 1994). Focal damage to the left dorsolateral prefrontal region has been associated with transcortical motor aphasia, which is characterized by nonfluent or semifluent speech with word finding difficulties but preserved repetition and comprehension. The left dorsolateral prefrontal cortex is also a crucial substrate for cognitive flexibility, abstract thinking, and various higher-level verbal cognitive abilities such as word associative fluency, discourse, verbal reasoning, verbal learning, and verbal working memory (Grattan, Bloomer, Archambault, & Eslinger, 1994; Petrides et al., 1993; Tulving et al., 1994). Recovery after unilateral damage to the dorsolateral prefrontal cortex often requires comprehensive neurorehabilitation services and medication management to improve attention and cognition (Cicerone et al., 2006; Eslinger et al., 1995; Mateer, 1997). Residual deficits will vary with hemisphere of lesion, as described above. Most individuals can return to independent home and some community activities, but it is often difficult to return to competitive employment and fully independent functioning. Bilateral damage is

Figure 20.3 Brain MRI scan showing right dorsolateral prefrontal lesion causing lefthemispatial neglect and inattention.

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Figure 20.4 Design copy and clock drawing of a patient with right dorsolateral prefrontal cortex lesion at 7 years of age. The figure shows neglect of left hemispace even at 6 months after lesion but progressive improvement that has been maintained over 8 years of follow-up studies.

generally associated with profound disability and cognitive, behavioral, and emotional impairments. Some medications can help improve behavioral, emotional, and cognitive symptoms, but these will not restore full functioning, and patients typically need to reside in a safe living environment with some degree of supervised care. Mesial frontal syndromes The mesial frontal region comprises primary motor and premotor cortices in its most superior extent, encompassing the supplementary motor cortex as well as anterior cingulate. Damage to these regions has been associated with disorders of motivation, behavioral initiation, and self-regulation (see Figure 20.5 for an example of a mesial frontal lesion). These disorders are summarized in Table 20.2 and include most prominently akinesia and mutism (the profound loss of intentional and goal-directed behavior as well as spontaneous speech and actions), apathy, and decreased motivation as well as disorders of intention, self-regulation, apraxia, and what is described as “alien hand”. Alien or anarchic hand may be a manifestation of

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Figure 20.5 MRI scan showing left superior mesial frontal lesion affecting pathways crossing in the corpus callosum and damaging the anterior cingulate and supplementary motor area.

disconnection in the region of the corpus callosum. For example, the left hand, typically under the control of the right motor regions, can appear to act on its own after crossing motor pathways are interrupted. Thus, the patient may articulate one intended action but undertake another with the left hand, since the two hemispheres are disconnected. In some instances, the left hand works in opposition to the right hand in dressing and problemsolving tasks such as block design. In recent case studies, focal stroke affecting the white matter of the left superior frontal gyrus (subjacent to Brodmann’s areas 9 posterior, 8 and rostral 6) has been associated with utilization behavior, which is a disorder of behavioral control (Ishihara, Nishino, Maki,

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Kawamura, & Murayama, 2002). Patients with utilization behavior show disinhibited use of objects within their environment and without respect to specific intentions or goal-directed behavior. For example, if there is an envelope with paper and pen on the table, the patient may pick up the pen and write a note (not necessarily of any relevance to the situation or an intended goal), fold and seal it in the envelope, and address it, all in perfect sequence, but then leave the letter on the table without any intention of mailing it. Such automatic actions appear to be triggered by stimuli that, in a sense, seem to invite the individual to utilize them without regard to situational appropriateness and personal goals. Bilateral strokes in the superior mesial region (Brodmann’s area 6 and part of 4 but sparing the anterior cingulate and corpus callosum) have been associated with akinesia and mutism that can evolve to clinical forms of tonic grasping, groping, and other frontal release reflexes that may last for many months (Boccardi, Della Sala, Motto, & Spinnler, 2002). The patient’s hands seem to act with a will of their own, utilizing whatever is within grasp. The authors suggested the term anarchic hands since the hands appear to act with minimal regulation and control. Both utilization behavior and anarchic hand are examples of release abnormalities, in which the deficit is manifested as impaired control of behavior. While previous accounts hypothesized that utilization behavior is a result of frontal-parietal disconnection, these recent case studies emphasized that the mesial frontal region is critically involved in regulating internally driven motor control. When this region is damaged, the clinical effect is release of externally prompted actions that depend entirely upon the cues and stimuli encountered by the patient (Eslinger, 2002). Dopamine agonists such as bromocriptine have been found in preliminary clinical studies to be helpful in ameliorating some aspects of the akinesia and mutism associated with mesial frontal damage (Eslinger et al., 1995). The inferior mesial frontal regions encompass cortical areas rostral and subjacent to the corpus callosum, including the subcallosal gyrus and medial gyrus rectus. These regions are part of neural networks that span cognition and emotion, as well as prefrontal-limbic-paralimbic systems. Damage to this region has been associated with behavioral disorders such as loss of personal contexts, loss of self-monitoring, loss of motivation, and memory impairment (Figure 20.6 shows such a lesion). For example, patients with damage to the inferior mesial prefrontal cortex may arrive at a job they held several years ago, not realizing that they have not worked there for some time. This may be prompted by seeing a work uniform in the closet or other cue around the house. Morphometric as well as functional imaging abnormalities in the subgenual region have been found in primary familial depression and bipolar disorder (Drevets et al., 1997).

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Figure 20.6 Brain MRI scan demonstrating a mesial prefrontal lesion that was associated with reduced motivation, emotion, and self-monitoring.

Ventral frontal syndromes The ventral frontal region comprises the basal forebrain, orbitofrontal cortex, and the deep white-matter regions that include the paraventricular areas. Damage to this portion of the frontal lobe is common after traumatic brain injury, and an example is shown in Figure 20.7. There is a continuum of impairments associated with ventral frontal damage, varying from transient changes in memory, emotions, and personality to profound change in personality, social judgment, goal-directed behavior, empathy, and emotion processing (Dimitrov et al., 1999; Eslinger & Damasio, 1985; Grafman, Vance, Weingartner, Salazar, & Amin, 1986). Such individuals may present somewhat similarly to Phineas Gage. Modern descriptions indicate that standardized measures of intellect, memory, and executive functions after ventral frontal damage may be entirely normal, despite profound impairment of judgment and self-regulation. It can be difficult to observe such deficits in a clinic or office setting, and family members may be the main informants of such impairments in everyday life. There are a number of behavior-rating scales that can be helpful in identifying frontal behavioral symptoms, and these were recently reviewed by Malloy and Grace (2005). Bechara, Damasio, Damasio, and Anderson (1994) were able to detect significant deficits in learning and self-monitoring in such patients by an experimental gambling task. Furthermore, they linked the deficits to impaired emotional and autonomic activation in processing positive and negative consequences of choices. Rolls, Hornak, Wade, and McGrath (1994) have also detected emotionrelated impairments in contingency-based learning (involving reward and

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Figure 20.7 Brain MRI showing a right ventral prefrontal lesion secondary to traumatic brain injury.

punishment) and emotional face as well as emotional voice recognition (Hornak, Rolls, & Wade, 1996; Rolls et al., 1994). There is also evidence for asymmetric patterns of deficits, with right ventral prefrontal damage leading to more disabling social-emotional impairments (Shamay-Tsoory, Tomer, Berger, Goldsher, & Aharon-Peretz, 2005; Tranel, Bechara, & Denburg, 2002). Damage to the posterior mesial portions of the ventral frontal region known as the basal forebrain can produce syndromes of memory loss that also involve confabulations and delusions. These presentations are typically associated with ruptured aneurysms of the anterior communicating artery and with orbital tumors. Within this area, there are many deep white-matter tracts that connect to the anterior temporal lobe, including the temporal pole and amygdala, as well as to the striatum, thalamus, and hypothalamus, providing critical pathways for coordination of input and output of cognitive and emotional processing (Cummings, 1993). Damage that disconnects these

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important pathways has been associated with poorer recovery and outcome (Grattan & Eslinger, 1991). Rehabilitation approaches have been described and appear to be of some benefit to patients with ventral prefrontal syndromes, particularly in improving goal-directed behavior under certain familiar conditions (Cicerone & Giacino, 1992; Levine, Freedman, Dawson, Black, & Stuss, 1999; Mateer, 1997), but clearly effective treatments are still being researched.

Prefrontal cortex and human development There are multiple phases of psychological growth and maturation during childhood and adolescence. These provide the foundation for adaptive, independent functioning as an adult and especially for social adjustment and behavior. Maturation of the brain is closely tied to these human developmental processes, but the linkages between neurobiology and development are still being identified (Krasnegor, Lyon, & Goldman-Rakic, 1997). Study of children with early damage to the prefrontal cortex has provided some seminal ideas about such linkages. Ackerly and Benton (1948) described the first modern case of early prefrontal cortex damage and development (case JP). This adolescent was brought for evaluation at the Louisville Mental Hygiene Clinic in 1926, when he was 13 years of age. He had persistent difficulty in getting along with classmates and other peers, often being boastful, bossy, and callous. Self-control was problematic with flagrant sexual misconduct and impulsivity. His judgment and planning were poor, and he was unable to learn from experience. Curiously, he showed no anxiety, interpersonal sensitivity, or fear of consequences. His measured intellect, speech and language, and perceptual abilities were within the average range. He could be socially engaging at times, but was unable to maintain friendships and even stable social relationships. Evaluation of JP revealed that he had probably suffered congenital damage to the prefrontal cortex, affecting right greater than left polar, medial, and orbital regions. We reconstructed his estimated brain lesion from surgical reports, and this is summarized in Figure 20.8. JP was followed over time, until he was a young adult (Ackerly, 1964; Benton, 1991a). His pattern of social and executive deficits persisted. Ackerly and Benton (1948) concluded that JP showed a primary social defect that was not explained by impaired intelligence, memory, or perception, by lack of literal social knowledge (he was described as having “an excellent sense of right and wrong when talking about it in an abstract manner, but showed no such sense in his actions”), or by abnormal parenting and acculturation. The early prefrontal cortical damage most likely prevented JP from acquiring social and moral self-regulation as well as the amplification and elaboration of personal experience that typically emerges in childhood and adolescence. Hence, his puerile social behavior might be considered a developmental reflection of incomplete prefrontal neural differentiation and the social-emotional maturation that it could manage to mediate.

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Figure 20.8 Reconstruction of the congenital bifrontal lesion of patient JP, based upon neurosurgeon’s description of the brain during exploratory surgery.

This remarkable pattern of impaired psychological development has been confirmed and extended in more recent case studies of patient DT, who acquired prefrontal cortical damage at 7 years of age (Eslinger, Grattan, & Damasio, 1992; Eslinger, Biddle, & Grattan, 1997). DT was first evaluated when she was 33 years of age, approximately 26 years after a focal prefrontal hemorrhagic lesion with surgical evacuation (see Figure 20.9 for lesion summary). She had an excellent medical recovery, but gradually developed progressive social and executive impairments in early adolescence, that have

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Figure 20.9 Template localization of left polar and mesial prefrontal lesion in patient DT, who suffered onset at age 7 years and was subsequently studied as an adult.

continued into adulthood. While she was premorbidly a well-adjusted child who participated well in school, she became more disorganized, disinhibited, and emotionally immature. She exhibited poor social judgment and was unable to develop stable relationships. Her learning and academic achievement declined. Throughout adolescence, she showed an arrest of social, cognitive, and emotional intelligence that persisted into adulthood. As an adult, DT was disabled and functionally dependent. She was unable to maintain employment, develop positive and supportive relationships, care for a child, and plan and organize her life. She had the benefit of medical and

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psychological treatment services as well as a supportive family, but remained immature and poorly adjusted. Although DT did not have the truant tendencies of the Ackerly and Benton (1948) case JP, she nevertheless showed a poor developmental outcome, with a simplistic and poorly integrated personality that centered on getting her immature social and emotional needs met. Her thinking was concrete and often overshadowed by emotional and selfregulatory deficits (see Anderson, Bechara, & Damasio, 1999, for similar cases). A recent comprehensive review of available cases with early prefrontal cortex damage concluded that early lesions affecting the orbital-medial and polar prefrontal regions are associated with profound developmental impairments that compromise a person’s ability to live, work, and function independently. This appears to be the case with unilateral and bilateral lesions though there may be outcome variations depending upon age of onset and extent of damage. In contrast, early unilateral lesions to dorsolateral prefrontal regions show a much more positive outcome, with mild residual executive and learning difficulties but preserved social and emotional adaptation (Eslinger, FlahertyCraig, & Benton, 2004). This has led us to consider that the neural integration of executive functions, social knowledge, and emotional processing is a major neurodevelopmental challenge and perhaps the centerpiece of adolescent and adult development.

Cognitive and emotional functions of the prefrontal cortex Knowledge, problem-solving, and memory Grafman (1995a; Wood & Grafman, 2003) has argued persuasively that the executive functions associated with the prefrontal cortex entail certain forms of knowledge that are unique to this brain region. As an area of associative cortex, the prefrontal region is well equipped anatomically and physiologically to acquire information and organize it into structures of long-term memory. He has proposed that executive knowledge encompasses structured event complexes that function as comparatively large memory units in support of planning, organization, and the goal-directed behaviors. Such complexes are composed of associated events that are organized sequentially and in parallel around a particular theme or goal (such as going to school, shopping for a car, or attending a funeral) and include acquired knowledge of social rules, concepts, and the various contingencies of each type of event. This theoretical framework permits experimental study of how people organize and regulate their behavior in relationship to specific goals in daily life. It shares some overlap with other important notions about the prefrontal cortex and cognition, including the supervisory attentional system (Shallice, 1988), cross-temporal contingencies of action (Fuster, 1991), and the parallel, hierarchical organization of cognition and emotion (Stuss & Benson, 1986). Another facet of prefrontal cognition is the type of problem-solving that it

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mediates. Standardized tests of general intelligence (such as the Wechsler IQ scales) have been found to be insensitive to the executive function deficits associated with prefrontal damage. In contrast to this crystallized form of intelligence, problem-solving approaches that entail relational reasoning and working memory have been described as fluid intelligence. This type of problem-solving does not depend upon specific memorized knowledge but rather on the use of strategies in determining novel solutions. A recent functional brain-imaging study has suggested that the dorsolateral prefrontal cortex is particularly important in the mediation of fluid IQ (Duncan et al., 2000). An example of such activation is shown in Figure 20.10 from an fMRI study of a healthy teenage volunteer in our laboratory using pattern-solving stimuli similar to the Raven’s Progressive Matrices. The BOLD effect on this anatomic image shows prominent prefrontal activity (networked with other regions) during the relational reasoning task.

Figure 20.10 fMRI illustration of prefrontal activation patterns occurring during a fluid IQ task in a typical subject. (This figure is published in color at www.psypress.com/brainscans-etc/)

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The role of the prefrontal cortex in helping structure and organize information during learning has been explored with the levels of processing paradigm. In this particular task, subjects are asked to make decisions about a series of common words, and then tested on their later recall of the words. Orienting questions include whether a particular letter is present in the word (visual feature level of processing), whether the word is a type of animal (semantic level of processing), or whether it may be descriptive of oneself (autobiographical level of processing). The effect of the orienting question is to bias the type of associative processing during the task and this in turn has a profound effect on later recall of the words. Those words that are processed at semantic and autobiographical levels are considered a deeper or richer associative level than the letter feature, which is a visual discriminative and more shallow level. Functional MRI study in our lab revealed that the deeper levels of processing and the higher memory recall are associated with coordinated prefrontal and hippocampal activity, as shown in Figure 20.11.

Figure 20.11 fMRI illustration of the levels of processing effect with predominant left dorsolateral prefrontal activity and left hippocampal activity during associative processing of words that required semantic decision-making and led to higher retention. (This figure is published in color at www.psypress.com/brainscans-etc/)

400 Eslinger The BOLD effects here show predominant activation in the left dorsolateral prefrontal region and the left hippocampus, supporting the importance of prefrontal–hippocampus interactions in associative learning. Metacognition Metacognition encompasses domains and processes of self-knowledge, selfmonitoring, and self-regulation that contribute to adaptive behavior in complex and changing environments (Mazzoni & Nelson, 1998; Metcalfe & Shimamura, 1996). Metacognition is considered the basis of personal awareness and personal knowledge. These are specialized forms of perception and knowledge that entail evaluative components of ourselves and our experiences across time, leading to a stable sense of identity. Metacognitive processing can be experimentally measured in certain ways. For example, subjects may be asked to predict their expected performance in a particular cognitive task, such as learning a word list. This entails applying self-knowledge of one’s abilities (derived from various prior experiences, incorporation of feedback, and self-reflection) and synthesis of that information for judgment purposes. Subjects can also be asked how hard or easy it will be to learn particular words. These judgments of learning measures require knowledge of stimulus characteristics and one’s prior experiences with those types of items. Aside from self-predictions, another dimension of metacognition can be measured by assessing subjects’ judgment of how they actually performed after completing a task. This aspect of metacognition emphasizes selfmonitoring and permits comparison of how subjects perceive and evaluate their performance with actual measured performance. Metacognitive processing has also been implicated in the self-regulation of behavior through central executive functions. This includes how effectively and accurately subjects can access and utilize self-knowledge and selfmonitoring abilities to guide their cognition and behavior in social and nonsocial contexts. Standardized behavioral rating scales provide the most common approach to surveying these functions in daily real-world settings, often with confirmatory information from caregivers and family members. Neurobehavioral studies of patients with focal cerebral lesions suggest that clinical disorders of self-awareness and metacognition can be associated with prefrontal pathophysiology and lead to adaptive deficits in daily functioning. Metacognitive impairments after prefrontal cortical damage include overestimation of one’s abilities, lack of awareness of newly acquired deficits, inability to learn from experience, and poor utilization of feedback about behavior in order to modify problem-solving approaches and strategies (Janowsky, Shimamura, & Squire, 1989; Vilkki, Servo, & Surma-Aho, 1998). These metacognitive impairments are often described as forms of anosognosia (lack of self-knowledge) that occur within problem-solving and socialemotional contexts even though general cognitive abilities remain intact. Selfawareness deficits should be evaluated at cognitive (what can one do and not

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do?) and emotional (what does this mean?) levels. Levine et al. (1999) have suggested that some forms of impaired self-regulation and metacognition may be related to deficits in re-experiencing personal episodic information that would typically guide responding in similar situations, particularly inhibition. A recent study of patients with frontotemporal dementia (FTD) revealed that those with prominent social impairments (or so-called frontal variant FTD) were profoundly impaired in self-awareness of their everyday deficits in comparison to patients with FTD-related language deficits, Alzheimer’s disease, and age-matched controls (Eslinger, Dennis, Moore, Antani, Hauck, & Grossman, 2005). Certain lines of research have linked metacognitive deficits to impaired executive functions mediated principally through prefrontal cortical systems, supporting an interrelationship between metacognition and executive functions. Social emotions and social cognition We naturally grow and reside within social and emotional contexts that entail interpersonal processes of emotion and cognition. Even as infants, we form numerous and diverse attachments that are the basis for sharing of emotions, experiences, and behavior. Emotions provide a variety of internal and physiological states that contribute to how we organize, prioritize, and respond to our social and nonsocial worlds. Rolls (1990) suggested that emotions are states that are produced by reinforcing stimuli. Primary reinforcers produce automatic or unconditioned states, while secondary reinforcers acquire their force through associative learning. For example, food can be considered a primary reinforcer that has innate reward value while money is a secondary reinforcer that acquires meaning and significance only through its association with potential rewards such as fine clothes, cars, a home, etc. The basic emotions of happiness, sadness, surprise, fear, disgust, and anger have strong cross-cultural reliability and are considered universal human attributes. In contrast, social emotions have been differentiated from basic emotions and conceptualized as emotions that are linked to the interests and welfare of others or to society as a whole (Moll, Oliveira-Souza, & Eslinger 2003). As a function of the increase in social complexity as human culture evolves, social emotions are one of the mechanisms to regulate and manage how we respond to and interact with others. Social emotions are generally invoked by circumstances that extend beyond the immediate sphere of the self, and can act to bring cohesiveness as well as dissolution to social groups and relationships. We have begun investigation of the neural bases of social emotions, particularly as they apply to notions of moral behavior. The results suggest that there is a network of brain areas specifically involved in social emotions such as moral judgments, moral violations, disgust, and contempt (see Figure 20.12 for summary). These brain regions include most prominently the orbital, mesial, and polar prefrontal cortices, the amygdala and temporal polar cortex, the superior temporal sulcus, and the insula.

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Figure 20.12 Summary of activation regions in the frontal and temporal lobes associated with social emotions from functional brain-imaging studies of typical adults (from Moll et al., 2003). (This figure is published in color at www.psypress.com/brainscans-etc/)

Another important set of mechanisms to regulate and manage how we respond to others involves cognitive processes known as theory of mind (ToM). ToM refers to the ability to think about and infer the mental states of others. ToM abilities are considered necessary not only for understanding and sharing the experiences of other persons but also for establishing their intentions and deciding how best to respond in social situations. Inferring the mental states of others follows a developmental course throughout childhood and is linked to emergence of empathy and stable relationships. ToM can be assessed through standardized measures such as first-order beliefs (what another person is thinking or believing) and second-order beliefs (what a person thinks another person is thinking or believing). These capacities have been associated with the prefrontal cortex through both lesion and functional imaging studies (Gregory et al., 2002; Stuss, Gallup, & Alexander, 2001; Vollm et al., 2006). Stimuli that have an affective ToM quality (that is, what we think another person feels) include social faux pas scenarios as well as irony and sarcasm. This type of mental-emotional inferential processing is reported to be impaired particularly after right ventromedial prefrontal cortex damage (Shamay-Tsoory et al., 2005). It is conceivable that the changes in personality and social functioning after

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orbital-medial prefrontal damage is related in part to impaired ToM abilities, both cognitive and affective. ToM provides a common platform and frame of reference for perceiving, thinking about, and understanding the mental and emotional states of others. This entails not only conceptualizing that others have minds that are separate from our own, but also understanding that others experience mental and emotional states. ToM deficits, therefore, can lead to more literal or concrete interpretation of the actions, intentions, and emotions of others and impaired empathy. There are likely to be somewhat separable neural substrates for cognitive and affective ToM, but also shared resources for such processing. ToM abilities have been shown to be dissociated from performance on standard tests of executive function, although it is reasonable to expect that they also share some executive resources in load of working memory, relational reasoning, and inferential processing. We analyzed these possibilities in a recent study of FTD patients (Eslinger, Moore, Troiani, Antani, Cross, Kwok, & Grossman, 2007). In comparison to FTD patients with primarily language deficits and to age-matched controls, the socially impaired FTD sample was much poorer in resolving standardized social dilemmas as well as in ToM, cognitive flexibility, and ratings of empathic behaviors. Regression analyses revealed that while these domains are intercorrelated, the cognitive flexibility measure was the most predictive of impaired social judgment. Furthermore, voxel-based morphometry revealed that the social dilemma impairments are correlated with atrophy in the orbitofrontal, superior temporal, visual association, and posterior cingulate regions in the right hemisphere. From these findings, which require confirmation in clinical samples with other forms of prefrontal pathophysiology, we hypothesize that deficits in social behavior and judgment can be related to depleted executive resources and social knowledge associated with damage to the right prefrontal-temporal neural networks mediating social cognition.

Summary The frontal lobe is a structurally and functionally complex brain region. Its primary motor and premotor cortices have been associated with motor learning, action, and control. The prefrontal cortex is a richly interconnected associative region that has been implicated in diverse cognitive, emotional, and social processes that center on executive, integrative, and self-regulatory aspects of adaptive behavior. As might be expected, damage to the prefrontal cortex often leads to significant behavioral deficits that will be expressed differently depending on the specific location and type of pathophysiology. Prominent frontal lobe syndromes can be identified for dorsolateral, mesial, and orbital regions of the prefrontal cortex, as well as for primary motor and premotor cortices, with contrasting effects of right versus left-sided damage. The prefrontal cortex has been increasingly implicated in cognitive and social-emotional development, with postnatal maturation extending through

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adolescence into adulthood. With the advent of functional brain-imaging methods, the role of the prefrontal cortex in the typical processes of cognition and social-emotional processing has been more clearly identified, particularly working memory, decision-making, ToM, and social cognition and emotions. Research will continue to focus on how this neural region mediates the interplay of cognitive and emotional processing systems in behavior and self-regulation over the lifespan.

References Ackerly, S. S. (1964). A case of paranatal bilateral frontal lobe defect observed for thirty years. In J. M. Warren & K. Albert (Eds.), The frontal granular cortex and behavior (pp. 192–218). New York: McGraw-Hill. Ackerly, S. S., & Benton, A. L. (1948). Report of a case of bilateral frontal lobe defect. Proceedings of the Association for Research in Nervous and Mental Disease, 27, 479–504. Alexander, G. E., Crutcher, M. D., & DeLong, M. R. (1990). Basal gangliathalamocortical circuits: Parallel substrates for motor, oculomotor, “prefrontal” and “limbic” functions. Progressive Brain Research, 85, 119–46. Anderson, S. W., Bechara, A., & Damasio, H. (1999). Long-term sequelae of prefrontal cortex acquired in early childhood. Developmental Neuropsychology, 18, 281–296. Barbas, H. (1995). Anatomic basis of cognitive-emotional interactions in the primate prefrontal cortex. Neuroscience and Biobehavioral Review, 19, 499–510. Barbas, H., & Pandya, D. N. (1989). Architecture and intrinsic connections of the prefrontal cortex in the rhesus monkey. Journal of Comparative Neurology, 286, 353–375. Barbas, H., & Pandya, D. N. (1991). Patterns of connections of the prefrontal cortex in the rhesus monkey associated with cortical architecture. In H. S. Levin, H. M. Eisenberg, & A. L. Benton (Eds.), Frontal lobe function and dysfunction (pp. 35–58). New York: Oxford University Press. Bechara, A., Damasio, A. R., Damasio, H., & Anderson S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7–15. Benton, A. L. (1991a). Prefrontal injury and behavior in children. Developmental Neuropsychology, 7, 276–281. Benton, A. L. (1991b). The prefrontal region: Its early history. In H. S. Levin, H. M. Eisenberg, & A. L. Benton (Eds.), Frontal lobe function and dysfunction (pp. 3–32). New York: Oxford University Press. Boccardi, E., Della Sala, S., Motto, C., & Spinnler, H. (2002). Utilisation behaviour consequent to bilateral SMA softening. Cortex, 38, 289–308. Bogousslavsky, J. (1994). Frontal stroke syndromes. European Journal of Neurology, 34, 306–315. Bottini, G., Corcoran, R., Sterzi, R., Paulesu, E., Schenone, P., Scarpa, P., et al. (1994). The role of the right hemisphere in the interpretation of figurative aspects of language. A positron emission tomography activation study. Brain, 117, 1241– 1253. Casey, B. J., Cohen, J. D., Jezzard, P., Turner, R., Noll, D. C., Trainor, R. J., et al.

20. Frontal lobe functions

405

(1995). Activation of prefrontal cortex in children during nonspatial working memory task with functional MRI. NeuroImage, 2, 221–229. Cicerone, K. D., & Giacino, J. T. (1992). Remediation of executive function deficits after traumatic brain injury. NeuroRehabilitation, 2, 12–22. Cicerone, K., Levin, H., Malec, J., Stuss, D., & Whyte, J. (2006). Cognitive rehabilitation interventions for executive function: Moving from bench to bedside in patients with traumatic brain injury. Journal of Cognitive Neuroscience, 18, 1212– 1222. Cummings, J. L. (1993). Frontal-subcortical circuits and human behavior. Archives of Neurology, 50, 873–880. Damasio, A. R., Tranel, D., & Damasio, H. C. (1991). Somatic markers and the guidance of behavior: Theory and preliminary testing. In H. S. Levin, H. M. Eisenberg, & A. L. Benton (Eds.), Frontal lobe function and dysfunction (pp. 217–229). New York: Oxford University Press. Damasio, H., Grabowsky, T., Frank, R., Galarirda, A. M., & Damasio, A. R. (1994). The return of Phineas Gage: Clues about the brain from the skull of a famous patient. Science, 264, 1102–1105. Dimitrov, M., Phipps, M., Zahn, T. P., & Grafman, J. (1999). A thoroughly modern Gage. Neurocase, 5, 345–354. Drevets, W. C., Price, J. L., Simpson, J. R. J., Todd, R. D., Reich, T., Vannier, M., et al. (1997). Subgenual prefrontal cortex abnormalities in mood disorders. Nature, 386, 824–827. Duncan, J., Seitz, R. J., Kolodny, J., Bor, D., Herzog, H., Ahmed, A., et al. (2000). A neural basis for general intelligence. Science, 289, 457–460. Eslinger, P. J. (1999). Orbital frontal cortex: Historical and contemporary views about its behavioral and physiological significance. An introduction to special topic papers. I. Neurocase, 5, 225–229. Eslinger, P. J. (2002). The anatomic basis of utilization behaviour: A shift from frontal-parietal to intra-frontal mechanisms. Cortex, 38, 273–276. Eslinger, P. J., Biddle, K. R. & Grattan, L. M. (1997). Cognitive and social development in children with prefrontal cortex lesions. In N. P. Krasnegor, G. R. Lyon, & P. S. Goldman-Rakic (Eds.), Development of the prefrontal cortex: Evolution, neurobiology, and behavior (pp. 295–335). Baltimore, MD: Paul H. Brookes. Eslinger, P. J., & Chakara, F. (2004). Frontal lobe and executive function. In M. Rizzo, & P. J. Eslinger (Eds.), Principles and practice of behavioral neurology and neuropsychology (pp. 435–456). Philadelphia: Elsevier. Eslinger, P. J., & Damasio, A. R. (1985). Severe disturbance of higher cognition after bilateral frontal lobe ablation: Patient EVR. Neurology, 49, 764–769. Eslinger, P. J., Dennis, K., Moore, P., Antani, S., Hauck, R., & Grossman, M. (2005). Metacognitive deficits in frontotemporal dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 76, 1630–1635. Eslinger, P. J., Flaherty-Craig, C., & Benton, A. L. (2004). Developmental outcomes after early prefrontal cortex damage. Brain and Cognition, 55, 84–103. Eslinger, P. J., Grattan, L. M., & Damasio, A. R. (1992). Developmental consequences of childhood frontal lobe damage. Archives of Neurology, 49, 764–769. Eslinger, P. J., Grattan, L. M., & Geder, L. (1995). Impact of frontal lobe lesions on rehabilitation and recovery from acute brain injury. NeuroRehabilitation, 5, 161–182. Eslinger, P. J., Moore, P., Troiani, V., Antani, S., Cross, K., Kwok, S., & Grossman, M.

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(2007). Oops! Resolving social dilemmas in frontotemporal dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 78, 457–460. Fuster, J. M. (1991). Role of the prefrontal cortex in delay tasks: Evidence from reversible lesion and unit recording in monkey. In H. S. Levin, H. M. Eisenberg, & A. L. Benton (Eds.), Frontal lobe function and dysfunction (pp. 66–71). New York: Oxford University Press. Goel, V., Gold, B., Kapur, S., & Houle, S. (1998). Neuroanatomical correlates of human reasoning. Journal of Cognitive Neuroscience, 10, 293–302. Goldman-Rakic, P. S. (1987). Circuitry of primate prefrontal cortex and regulation of behavior by representational memory. In H. S. Levin, H. M. Eisenberg, & A. L. Benton (Eds.), Handbook of physiology, the nervous system V (pp. 72–91). New York: Oxford University Press. Grafman, J. (Ed.) (1995a). Structure and function of the human prefrontal cortex. Annals of the New York Academy of Sciences, 769, 1–411. Grafman, J. (Ed.) (1995b). Similarities and distinctions among current models of prefrontal cortical functions. Annals of the New York Academy of Sciences 769, 337–368. Grafman, J., Vance, S. C., Weingartner, H., Salazar, A. M., & Amin, D. (1986). The effects of lateralized frontal lesions on mood regulation. Brain, 109, 1127–1148. Grattan, L. M., Bloomer, R. H., Archambault, F. X., and Eslinger, P. J. (1994). Cognitive flexibility and empathy after frontal lobe lesion. Neuropsychiatry, Neuropsychology, and Behavioral Neurology, 7, 251–259. Grattan, L. M., & Eslinger, P. J. (1991). Characteristics of favorable recovery from frontal lobe damage. Neurology, 41, 266. Gregory, C., Lough, S., Stone, V., Erzinclioglu, S., Martin, L., Baron-Cohen, S., et al. (2002). Theory of mind in patients with frontal variant frontotemporal dementia and Alzheimer’s disease: Theoretical and practical implications. Brain, 125, 752–764. Harlow, J. M. (1848). Passage of an iron bar through the head. Boston Medical and Surgical Journal, 39, 389–393. Harlow, J. M. (1868). Recovery from passage of an iron bar through the head. Publications of the Massachusetts Medical Society, 2, 327–347. Hornak, J., Rolls, E. T., & Wade, D. (1996). Face and voice expression identification in patients with emotional and behavioral changes following ventral frontal lobe damage. Neuropsychologia, 34, 247–261. Ishihara, K., Nishino, H., Maki, T., Kawamura, M., & Murayama, S. (2002). Utilisation behaviour as a white matter disconnection syndrome. Cortex, 38, 379–387. Janowsky, J. S., Shimamura, A. P., & Squire, L. R. (1989). Memory and metamemory: Comparison between patients with frontal lobe lesions and amnesic patients. Psychobiology, 17, 3–11. Jonides, J., Smith, E. E., Koeppe, R. A., Awh, E., Minoshima, S., & Mintun, A. (1993). Spatial working memory in humans as revealed by PET. Nature, 363, 623–625. Krasnegor, N. A., Lyon, G. R., & Goldman-Rakic, P. S. (Eds.) (1997). Development of the prefrontal cortex: Evolution, neurobiology, and behavior. Baltimore, MD: Paul H. Brookes. Levin, H. S., Eisenberg, H. M., & Benton, A. L. (Eds.) (1991). Frontal lobe function and dysfunction. New York: Oxford University Press.

20. Frontal lobe functions

407

Levine, B., Freedman, M., Dawson, D., Black, S., & Stuss, D. T. (1999). Ventral frontal contribution to self-regulation: Convergence of episodic memory and inhibition. Neurocase, 5, 262–275. Marlowe, W. (1992). The impact of right prefrontal lesion on the developing brain. Brain and Cognition, 20, 205–213. Mateer, C. A. (1997). Rehabilitation of individuals with frontal lobe impairments. In J. Leon-Carrion (Ed.), Neuropsychological rehabilitation: Fundamentals, innovations and directions (pp. 285–300). Debray Beach, FL: GR/St Lucia Press. Mazzoni, G., & Nelson, T. O. (1998). Metacognition and cognitive neuropsychology. Mahwah, NJ: Lawrence Erlbaum Associates, Inc. Mega, M. S., & Cummings, J. L. (1994). Frontal-subcortical circuits and neuropsychiatric disorders. Neuropsychiatry and Clinical Neuroscience, 6, 358–370. Mesulam, M.-M., & Mufson, E. J. (1982). Insula of the Old World monkey. I. Architectonics in the insulo-orbito-temporal component of the paralimbic brain. Journal of Comparative Neurology, 212, 1–22. Metcalfe, J., & Shimamura, A. P. (1996). Metacognition: Knowing about knowing. Cambridge, MA: MIT Press. Miller, B. L., & Cummings, J. L. (Eds.) (2007). The human frontal lobes (2nd ed.). New York: Guilford Press. Moll, J., Oliveira-Souza, R., & Eslinger, P. J. (2003). Morals and the human brain: A working model. Neuroreport, 14, 299–305. Nauta, W. J. H. (1971). The problem of the frontal lobe: A reinterpretation. Journal of Psychiatric Research, 8, 167–187. Neafsey, E. J. (1990). Prefrontal cortical control of the autonomic nervous system: Anatomical and physiological observations. Progressive Brain Research, 85, 147–165. Petrides, M., Alivisatos, B., Meyer, E., & Evans, A. C. (1993). Functional activation of the human frontal cortex during the performance of verbal working memory tasks. Proceedings of the National Academy of Sciences of the USA, 90, 878–882. Porrino, L. J., Crane, A. M., & Goldman-Rakic, P. S. (1981). Direct and indirect pathways from the amygdala to the frontal lobe in the rhesus monkey. Journal of Comparative Neurology, 198, 121–136. Price, J. L. (1999). Networks within the orbital and medial prefrontal cortex. Neurocase, 5, 231–241. Price, J. L., Carmichael, S. T., & Drevets, W. C. (1996). Networks related to the orbital and medial prefrontal cortex: A substrate for emotional behavior? Progressive Brain Research, 107, 523–536. Rolls, E. T. (1990). A theory of emotion, and its application to understanding the neural basis of emotion. Cognition and Emotion, 4, 161–190. Rolls, E. T., Hornak, J., Wade, D., & McGrath, J. (1994). Emotion-related learning in patients with social and emotional changes associated with frontal lobe damage. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 1518–1524. Shallice, T. (1988). From neuropsychology to mental structure. New York: Cambridge University Press. Shamay-Tsoory, S. G., Tomer, R., Berger, B. D., Goldsher, D., & Aharon-Peretz, J. (2005). Impaired “affective theory of mind” is associated with right ventromedial prefrontal damage. Cognitive and Behavioral Neurology, 18, 55–67. Sirigu, A., Zalla, T., Pillon, J., Grafman, J., Agid, Y., & Dubois, B. (1995). Selective impairments in managerial knowledge following prefrontal cortex damage. Cortex, 31, 301–316.

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Stuss, D., & Benson, D. F. (1986). The frontal lobes. New York: Raven Press. Stuss, D. T., Gallup, G. G., Jr., & Alexander, M. P. (2001). The frontal lobes are necessary for “theory of mind”. Brain, 214, 279–286. Stuss, D. T., Gow, C. A., & Hetherington, C. R. (1992). “No longer Gage”: Frontal lobe dysfunction and emotional changes. Journal of Consulting and Clinical Psychology, 60, 349–359. Stuss, D. T., & Knight, R. T. (Eds.) (2002). Principles of frontal lobe function. New York: Oxford University Press. Thorpe, S. J., Rolls, E. T., & Maddison, S. (1983). Neuronal activity in the orbitofrontal cortex of the behaving monkey. Experimental Brain Research, 49, 93–115. Tranel, D., Anderson, S. W., & Benton, A. L. (1994). Development of the concept of “executive function” and its relationship to the frontal lobes. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology, (vol. 9, pp. 125–148). New York: Elsevier. Tranel, D., Bechara, A., & Denburg, N. L. (2002). Asymmetric functional roles of right and left ventromedial prefrontal cortices in social conduct, decision-making, and emotional processing. Cortex, 38, 589–612. Tulving, E., Kapur, S., Craik, F. I., Moscovitch, M., & Houle, S. (1994). Hemispheric encoding/retrieval symmetry in episodic memory: Positron emission tomography findings. Proceedings of the National Academy of Sciences of the USA, 91, 2016–2020. Vilkki, J., Servo, A., & Surma-Aho, O. (1998). Word list learning and prediction of recall after frontal lobe lesions. Neuropsychology, 12, 268–277. Vollm, B. A., Taylor, A. N., Richardson, P., Corcoran, R., Stirling, J., McKie, S., et al. (2006). Neuronal correlates of theory of mind and empathy: A functional magnetic resonance imaging study in a nonverbal task. Neuroimage, 29, 90–98. Wood, J. N., & Grafman, J. (2003). Human prefrontal cortex: Processing and representational perspectives. Nature Reviews Neuroscience, 4, 139–147.

SECTION VI

Memory disorders and neurodegenerative diseases

21 Memory Structure, function, and dysfunction Olivier Piguet and Suzanne Corkin

We do not remember. A certain group of our little people do this for us. They live in that part of the brain which has become known as the “fold of Broca”. [. . .] There may be twelve or fifteen shifts that change about and are on duty at different times like men in a factory. [. . .] Therefore it seems likely that remembering a thing is all a matter of getting in touch with the shift that was on duty when the recording was done. (Thomas Edison, quoted in Runes, 1948, pp. 209–213)

Memory helps define who we are as human beings and as individuals. It contributes to our notion of self and our sense of continuity in daily life and in the world. The fascination with memory is pervasive, for example, in the arts: painting, literature, and movies. Salvador Dali’s Persistence of Memory (aka The soft watches) painted in 1931 and Disintegration of the Persistence of Memory painted 20 years later are two works exploring the notion of the subjectivity of recollection and the dissolution of memory traces over time. One Hundred Years of Solitude, the novel by Nobel Prize winner Gabriel García Márquez, published in 1967, follows the Buendia family over several generations. The author describes one incident that underlies the importance of sleep in the formation and maintenance of memories. For reasons unknown, all the residents of the town where the Buendia family reside develop insomnia. This episode is followed by a progressive amnesia in which the inhabitants slowly begin to lose the names of objects and animals and their purpose. To fight this disorder, the villagers begin attaching labels to every object, plant, and animal stating its name and function or role: “This is the cow. She must be milked every morning.” Later on, just as mysteriously, the insomnia and the amnesia dissipate. Another particularly poignant book is John Bayley’s meticulous account of the slow and devastating effect of Alzheimer’s disease on memory, and the progressive mental disintegration of his wife, the writer Iris Murdoch (Bayley, 1999). Movies have also explored memory, as in Citizen Kane, in which the magnate’s last word on his deathbed, “Rosebud”, alluded to a powerful childhood memory. More recent examples are Memento, The Bourne Supremacy, and Minority Report, in

412 Piguet and Corkin which central characters face adversity and succeed despite severe memory disturbances. In the scientific community, the interest in these complex and fascinating cognitive functions has continued unabated since Ebbinghaus’ first experiments in the last quarter of the nineteenth century. Ebbinghaus pioneered the systematic exploration of memory, often using himself as a subject, and introduced such concepts as learning, learning curve, and retention of information over time (Ebbinghaus, 1885/1913). Evidence of the fascination with memory is the steady increase in the number of peer-reviewed publications on the topic over the years. A literature search in PubMed using the keywords memory disorders, limited to adults, generated 869 original publications, including 21 review articles for the 1970–9 period. These numbers increased to 1242 articles (51 reviews) in 1980–9 and 2149 articles (153 reviews) in 1990–9, to reach 1787 articles (93 reviews) for the period January 2000– December 2004. By the end of the first decade of the twenty-first century, the number of publications on memory disorders is likely to be double that of the preceding decade. This surge in publication rate is probably the result of recent technological developments in neuroimaging, such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). These instruments have proven useful for the exploration of cognitive processes, including memory, and have allowed investigators to address issues that were not previously amenable to experimentation. Since the early 1970s, the questions asked about memory have changed considerably, from investigating the domains and tasks on which amnesic patients are impaired to identifying memory capacities that are preserved, despite the presence of amnesia. This change reflects a shift in focus from declarative memory (episodic and semantic) to nondeclarative (or implicit) memory, exploring capacities such as skill learning, repetition priming, and classical conditioning. In parallel to lesion studies, investigations of memory substrates in unimpaired individuals throughout the life span have continued. More recently, there has been a surge of interest in the impact of emotion on memory performance and the modulation of memory by emotional content. This chapter proposes to map advances made over the past three decades in the understanding of human adult memory and memory disorders. We present a summary of the neuroanatomy of memory and review the main theoretical contributions to the field, including recent findings on emotional memory. Disorders secondary to developmental or congenital diseases are beyond the scope of this chapter and are not reviewed.

Neuroanatomy of memory The neural structures that support memory processes were first identified from lesion studies. The most famous patient is undoubtedly H.M., who, at the age of 27 years, underwent bilateral removal of the rostral portion of his medial temporal lobe (MTL) for the relief of intractable epilepsy (Corkin,

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Amaral, Gonzalez, Johnson, & Hyman, 1997; Scoville & Milner, 1957). This operation resulted in a dense global amnesia for day-to-day events and factual information that remains unchanged to this date, 52 years later. H.M. remains the reference against which new findings in the area of memory research and other cases of severe amnesia are compared (Corkin, 1984, 2002). The tragic outcome of H.M.’s operation underscored the importance of the role of MTL structures in memory function. This brain region includes the hippocampal formation (dentate gyrus, Ammon’s horn, and subiculum); the entorhinal, perirhinal, and parahippocampal cortices; and the amygdala (Figure 21.1) (Insausti & Amaral, 2004). The amygdala, which is located directly anterior to the hippocampus and has direct connections to the hippocampus and the limbic system, participates in the processing of emotional information. The entorhinal cortex is the principal source of input to the hippocampus, while the entorhinal, perirhinal, and parahippocampal cortices have reciprocal connections with various neocortical regions and association cortices (Suzuki & Eichenbaum, 2000). Bilateral damage to MTL structures results in an impairment in long-term memory: memory after a delay with distraction. The amnesia is observed regardless of the way in which memory is tested (such as recall, recognition, or learning to criterion), and regardless of the sensory modality through which the to-be-learned

Figure 21.1 Medial aspect of the left hemisphere after bisection along the midline, showing the main stuctures of the medial temporal region. 1, rhinal sulcus; 2, collateral sulcus; 3, intrarhinal sulcus; 5, gyrus ambiens; 6, entorhinal cortex; 8, uncus; 9, hippocampal fissure; 10, sulcus semiannularis; 11, gyrus semilunaris; 12, mammillary bodies; 13, anterior commissure; 14, pre-commissural fornix; 15, post-commissural fornix; 16, thalamus; 17, optic chiasm; 21, corpus callosum (rostrum); 22, corpus callosum (splenium); 24, gyri Andreae Retzii. From Insausti & Amaral (2004), with permission from Elsevier.

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material is presented. In contrast, immediate memory, the online maintenance of information, remains unaffected (Wickelgren, 1968), as do other aspects of memory that do not rely on conscious or intentional encoding and recollection (implicit or nondeclarative memory). Thus, the key deficit in amnesia is in converting short-term memory into long-term memory. Within the thalamus, the ventral aspect of the dorsomedial nucleus, intralaminal tract, and internal medullary lamina are brain structures also known to result in amnesia when damaged (Graff-Radford, Tranel, Hoesen, & Brandt, 1990; Squire, Amaral, Zola-Morgan, Kritchevsky, & Press, 1989). These nuclei are part of a circuit that includes the fornices and the mammillary nuclei, which are heavily connected to the MTL region. Amnesia has been reported following lesions in this region due to thalamic strokes (Winocur, Oxbury, Roberts, Agnetti, & Davis, 1984) as well as heavy alcohol abuse leading to Wernicke–Korsakoff syndrome (Butters, 1985; Mair, Warrington, & Weiskrantz, 1979). The amnesia is believed to be caused by a disconnection between thalamic and MTL structures (Malamut, Graff-Radford, Chawluk, Grossman, & Gur, 1992; Warrington & Weiskrantz, 1982). The basal forebrain is another critical region for memory function. Located at the junction of the cerebral hemispheres ventrally, the basal forebrain includes the substantia innominata, which projects to the hippocampus and the amygdala. The basal forebrain also comprises the nucleus basalis of Meynert, a collection of cholinergic neurons that project widely to the cortex and the limbic system. Significant cell loss occurs in the nucleus basalis of Meynert in Alzheimer’s disease (Mesulam, Shaw, Mash, & Weintraub, 2004; Rinne, Paljarvi, & Rinne, 1987) and in Wernicke–Korsakoff syndrome (Cullen, Halliday, Caine, & Kril, 1997), two diseases characterized clinically by significant memory disturbance. These findings support the role of the neurotransmitter acetylcholine in memory function. In the last decade, acetylcholinesterase inhibitors, such as donepezil, have been used increasingly to treat early and mild Alzheimer’s disease, albeit with mixed success. These medications delay the breakdown of acetylcholine following its release in the intersynaptic cleft, and thus increase the likelihood for acetylcholine molecules to bind with the muscarinic postsynaptic receptors, these receptors being largely spared in Alzheimer’s disease. The role of the prefrontal cortex (PFC) in memory operations received little attention in the early clinical literature, probably because PFC lesions do not result in amnesia, and patients with such lesions generally show normal performance on formal tests of memory, such as the Wechsler Memory Scale (Petrides, 1996). Nevertheless, discrete lesions of areas within the PFC in monkeys and man do interfere with the ability to perform particular mnemonic operations, including temporal ordering (Fustur, 2001; Milner, Petrides, & Smith, 1985), working memory (Petrides, 1994; Petrides & Milner, 1982), conditional associative learning (Petrides, 1987), memory for source (Janowsky, Shimamura, & Squire, 1989), and prospective memory (Shimamura, Janowsky, & Squire, 1990). Moscovitch and Winocur (2002) have

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emphasized the importance of the PFC in implementing strategic processes that are critical for encoding, retrieval, monitoring, searching, and verification. Numerous fMRI studies have uncovered further specialization within the dorsolateral and inferior PFC. Activation has been reported in Brodmann areas (BA) 6, 8, 10, 9/46, 44/6, and 45/47 during encoding (e.g. Golby et al., 2001; Kensinger, Clarke, & Corkin, 2003; Kensinger & Corkin, 2004; Wagner et al., 1998b); in BA 10, 45/47, and 10/46 during item recognition (e.g. Rugg, Henson, & Robb, 2003); and in BA 6, 8, 9, and 46 during source recognition (Dobbins, Rice, Wagner, & Schacter, 2003) (Figure 21.2). Further, Poldrack and Wagner (2004) make a strong argument for a dissociation of function within the left inferior prefrontal cortex (LIPC) (BA 45 and 47). According to these authors, the anterior and ventral part of the LIPC supports semantic (meaning-based) processing, whereas the posterior and dorsal part of the LIPC mediates phonological (speech-sound-based) processing. This position, however, is disputed by Thompson-Schill and colleagues, who have proposed that this region mediates selection of information from semantic memory (Thompson-Schill, D’Esposito, Aguirre, & Farah, 1997; Thompson-Schill et al., 1998).

Figure 21.2 Lateral view of the brain, showing the different Brodmann areas of the frontal lobe. Depicted are the areas of activation during working memory (blue), encoding (purple), item recognition (green), and source recognition (yellow) tasks. Adapted from Damasio (1991), Figure 5.4, from Frontal Lobe Function and Dysfunction, edited by Harvey S. Levin, H. M. Eisenberg, & A. L. Benton, copyright © 1991 by Oxford University Press, Inc. Used by permission of Oxford University Press, Inc. (This figure is published in colour at www.psypress.com/brainscans-etc/)

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Memory definitions and models By differentiating primary (short-term) memory from secondary (longterm) memory, William James was among the first to posit a multiplesystems model of memory. Despite considerable refinements since James’ proposal (James, 1890), this dichotomy remains essentially accurate to this day. The past three decades have seen major theoretical contributions to our understanding of memory function. One contribution is the conceptualization of long-term memory as two separate entities: a declarative and a nondeclarative memory system. Declarative memory denotes a type of memory that is explicit, in that it requires awareness and attention-demanding cognitive processes. Declarative memory has been referred to as knowing that (Cohen & Squire, 1980). In contrast, nondeclarative memory denotes implicit memory, which is without awareness and reflects the nonconscious aspects of memory. It includes skill learning, such as driving a car or touch-typing, as well as habit learning, classical conditioning, and repetition priming. In contrast to declarative memory, nondeclarative memory has been called knowing how. Another important contribution to our understanding of long-term memory is the distinction within declarative memory between episodic and semantic memory proposed by Tulving (1972, 1983). For example, when you think about the last time you went out to a restaurant for a meal, what you ordered, who accompanied you, and what the conversation was about, you essentially rely on episodic memory to retrieve the details that are specific to this event. Episodic memory comprises events that have an individual “signature”. These events are constrained in time and space, have specific content, and are, therefore, unique. For Tulving (2002), episodic memory is a uniquely human cognitive ability that contributes to consciousness (what Tulving calls autonoesis) and allows human beings to be aware of subjective time and of the capacity to travel back in time (that is, to revisit past events). Recently, however, Fortin and colleagues (Fortin, Wright, & Eichenbaum, 2004) demonstrated the presence of recollective-like memory processes in rats, suggesting the presence of episodic memory. Whether rats and other mammals possess the capacity to revisit past events voluntarily remains controversial. In contrast to episodic memory, when one tries to remember the capital of the Sultanate of Oman (Muscat), the chemical formula of water (H2O), or whether oil floats on water (yes), one relies on semantic memory. This type of memory is memory for facts. It reflects knowledge that is atemporal and unconstrained by time, in that it is not directly and uniquely linked to a particular event or occasion. As Tulving noted, semantic memory is not limited to man and is present in many animals that develop knowledge of the world and are capable of learning without having a clear awareness of this information (as when your cat knows to avoid your dog). Contributions to the taxonomy of memory in the past 30 years have not been limited to long-term memory. An important addition is the model of

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working memory proposed by Allan Baddeley and Graham Hitch (Baddeley, 1986; Baddeley & Hitch, 1974). Working memory refers to a working space allowing time-limited and content-limited storage and manipulation of information. This temporary storage takes place either in a verbal (phonological loop) or in a visual (visuospatial sketchpad) format (Figure 21.3). The working memory model further includes another component that acts upon the information available in the verbal and visual storage spaces: the central executive. In Baddeley’s model, the phonological loop and visuospatial sketchpad are slave systems at the beck and call of the central executive. In other words, the central executive is an attentional control system that manipulates and integrates the available information and links it to long-term memory, thereby generating novel representations. More recently, Baddeley (2000) expanded his original model to include an “episodic buffer”, an interface between the immediate, time-limited, and content-limited working space and the more permanent, atemporal, and content-unlimited long-term memory. When first proposed, working memory was a cognitive model and did not postulate specific underlying neurological structures (Baddeley, 1998). Insightful work in monkeys and man pointed to an important role of the dorsolateral PFC in working memory, and, more specifically, the anterior

Figure 21.3 Working memory model based on Baddeley (1986). This model posits an attentional control system (the central executive) that manipulates and integrates information from two slave systems (the phonological loop and the visuospatial sketchpad). The phonological loop is responsible for maintaining speech-based information in short-term memory (as in comprehension of a long, complex sentence). The visuospatial sketchpad performs a similar function in setting up and manipulating visuospatial imagery in short-term memory (as in playing chess). Each slave system can be divided further into a passive storage system and an active rehearsal system.

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portion of the middle frontal gyrus (BA 9 and 46), although investigators have debated its specific role. Goldman-Rakic (1987) postulated the existence of topographically segregated, modality specific units within the lateral PFC. The regional functional organization was posited to be an extension of the ventral/dorsal stream (“what” versus “where”) described in the visual system, with the dorsal PFC processing working memory for spatial location and the ventral PFC processing working memory for objects (Rao, Rainer, & Miller, 1997; Wilson, Scalaidhe, & Goldman-Rakic, 1993). Rao, Rainer, and Miller (1997), however, found that about half of PFC neurons in awake monkeys responded to both what and where information, casting doubt on the idea of strict segregation of object identity and location in working memory. Petrides and colleagues (Petrides, 1996) also disputed the separation of spatial and object working memory and instead proposed a hierarchical model of working memory. Their theory of PFC organization makes a distinction between capacities subserved by the mid-dorsolateral (BA 9 and 46) and the midventrolateral (BA 45 and 47/12) frontal cortex. The mid-dorsolateral frontal cortex is specialized for monitoring and manipulating information within working memory. For example, this area is critical for performance on self-ordered choosing tasks (Petrides, 1991, 1994). In contrast, the midventrolateral frontal cortex supports short-term memory for modality-specific and multimodal information. This theory posits that processing occurs first in the ventrolateral frontal cortex and then in the dorsolateral frontal cortex, such that working memory is a two-stage process (Petrides, 1994). This view has received support from neuroimaging studies (e.g. D’Esposito, Postle, Ballard, & Lease, 1999; Owen, Evans, & Petrides, 1996; Petrides, Alivisatos, Meyer, & Evans, 1993; Postle, Stern, Rosen, & Corkin, 2000).

Memory impairment in healthy aging Decline in memory function is the most common complaint associated with aging. Most instances of poor memory refer to a breakdown in episodic memory, with deficits taking the form of failure to remember appointments, names of people, or where personal objects, such as glasses, keys, or wallet, are located. New knowledge about memory and about prevalent diseases such as Alzheimer’s disease has led to a greater awareness of changes in memory, and raises the question of whether these changes represent a facet of healthy aging or reflect something more sinister. Performance differences between young and older adults on measures of episodic memory are well documented. Older people’s ability to encode novel information efficiently into memory is impaired. This impairment probably reflects inability to use self-initiated, cognitive control processes spontaneously due to age-related cortical and white-matter changes in the prefrontal region (Double et al., 1996; Salat, Kaye, & Janowsky, 1999). Interestingly, retention of the information over time can be improved by compensating for the encoding deficit (Glisky, Rubin, & Davidson, 2001). Retrieval of information is particularly

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affected in situations requiring spontaneous recollection—in other words, free recall. A striking example is the impaired ability of older adults to remember names. Performance improves with the provision of cues (cued recall) and even more so when they use a recognition format, such as old–new or remember–know recognition paradigms. Thus, it appears that, for declarative memory, older adults experience difficulty whenever there is a greater need for self-initiated strategies and whenever environmental support decreases, during either the encoding or the retrieval phase. Underuse of cognitive control processes is also reflected in difficulty with prospective memory (i.e. the ability to plan ahead) (Craik, 1986; West, Jakubek, & Wymbs, 2002) and with certain aspects of working memory (i.e. the ability to retain information temporarily while operating on it) (Baddeley & Hitch, 1974; Braver, Cohen, & Barch, 2001). In marked contrast, semantic memory and most aspects of nondeclarative memory are more resilient to the effects of aging, with little or no change in performance observed across decades. One exception is classic conditioning where older adults are impaired in learning to associate a neutral stimulus (such as a sound) with a relevant noxious stimulus (such as a puff of air on the eye) compared to young adults (Knuttinen, Power, Preston, & Disterhoft, 2001). This deficit probably reflects age-related cell loss in the cerebellum, a structure known to be critical for classic conditioning (Woodruff-Pak, Goldenberg, Downey-Lamb, Boyko, & Lemieux, 2000).

Material-specific memory impairment and global amnesia Apart from age-related processes, a number of acquired brain insults result in memory deficits during adulthood. Although the etiology of these insults is variable, all invade regions that are crucial to proper memory functioning: the MTL, diencephalon, and basal forebrain. For over four decades, Brenda Milner, at the Montreal Neurological Institute, has been studying memory capacities following unilateral frontal or temporal lobectomy for the relief of intractable epilepsy. She and others have demonstrated that the severity and kind of memory disturbance depend on the side, locus, and extent of the lesion. Unilateral temporal lobectomy gives rise to material-specific episodic memory deficits (Milner, 1978, 1985). In left-hemisphere-dominant individuals (who have language representation in the left hemisphere), a left-sided resection results in a deficit in memory tasks comprising a verbal component (as in short stories, word lists, etc.). In contrast, a lesion in the homologous structure in the right hemisphere results in impaired memory for visual and visuospatial material (Milner, 1971; Petrides & Milner, 1982). Often, the severity of the memory deficit is directly correlated with the extent of the hippocampal resection. Interestingly, for the small number of individuals with language representation in the right hemisphere (comprising less than 40% of left-handed individuals), milder deficits tend to follow unilateral lesions, possibly because of a more bilaterally distributed language representation

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(Josse & Tzourio-Mazoyer, 2004). The lateralization of memory deficits has been replicated in other disorders (such as stroke and traumatic brain injury), confirming the crucial role of the hippocampus, basal forebrain, and diencephalic structures in memory function. Acquired semantic memory deficits have also been documented. Loss in general knowledge and atemporal factual information is observed in semantic dementia, Alzheimer’s disease, and herpes simplex encephalitis. This deficit is generally associated with neocortical damage to the anterolateral or posterolateral temporal region in the dominant hemisphere (Hodges & Patterson, 1997), underscoring the importance of neocortical structures for the very long-term storage of facts and probably episodes. Chronic global amnesia is typically seen only with bilateral lesions (Squire, 1992). The most common etiologies are listed in Table 21.1 (see also Corkin et al., 1985; Tranel, Damasio, & Damasio, 2000). At clinical presentation, there is a consistent inability to retain novel information over time reliably. This deficit is material nonspecific and modality nonspecific. In other words, globally amnesic patients show impaired memory performance whether the

Table 21.1 Etiologies of chronic global amnesia Etiology

Locus of bilateral lesions causing amnesia

Selected references

Hypoxia Herpes simplex encephalitis Stroke

Hippocampus Medial temporal lobe region

(Squire & Zola, 1996) (Wilson, Baddeley, & Kapur, 1995) (Graff-Radford et al., 1990; Markowitsch, von Cramon, & Schuri, 1993; Yoneoka et al., 2004) (Alexander & Freedman, 1984; Bondi, Kaszniak, Rapcsak, & Butters, 1993; D’Esposito, Alexander, Fischer, McGlinchey-Berroth, & O’Connor, 1996) (Butters & Cermak, 1980; Fama, Marsh, & Sullivan, 2004; Visser et al., 1999) (Demery, Hanlon, & Bauer, 2001; Mattioli, Miozzo, & Vignolo, 1999) (Braak et al., 1996; Locascio, Growdon, & Corkin, 1995)

Dorsomedial nucleus of thalamus, medial temporal lobe region

Anterior communicating artery aneurysm

Basal forebrain, posterior inferior medial frontal region

Korsakoff syndrome

Tissue surrounding lateral, third and fourth ventricles, mammillary bodies Diffuse axonal injury, medial temporal lobe lesion

Closed head injury

Alzheimer’s disease

MTL structures, basal forebrain

Less common etiologies include bilateral medial temporal lobe resection (as in patient H.M.), penetrating head injury with transection of the fornix (Grafman, Salazar, Weingartner, Vance, & Ludlow, 1985), and ingestion of domoic acid from shellfish (Perl et al., 1990).

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information to be learned is verbal or spatial, and whether the stimuli are presented via the visual, auditory, somatosensory, or olfactory modality. This anterograde amnesia is often accompanied by retrograde amnesia, that is, impairment in remembering information that was encoded before the time of the lesion. In some cases, retrograde amnesia is temporally graded, with poorer memory for more recently acquired information and better memory for older information (Ribot, 1881). Another global memory disturbance, but of temporary nature, is the phenomenon of transient global amnesia. This deficit is characterized by an abrupt onset of a global amnesia lasting minutes to hours. It affects men and women equally, mostly in their 50s or over (Pantoni, Lamassa, & Inzitari, 2000). For the duration of the episode, the person is unable to form new memories (anterograde amnesia) and shows a patchy retrograde amnesia, particularly for events immediately preceding the episode. The patient’s identity, personal information, and semantic knowledge are preserved. The presentation is that of a perplexed person asking where she is and what is happening to her, and repeating the same questions over and over because she is unable to remember the responses to her queries. Transient global amnesia is generally not accompanied by stress or anxiety, or by any motor or sensory deficits. Not uncommonly (about 30% of cases), transient global amnesia is preceded by an episode of heightened activity, immersion in cold water, intense emotion, sexual intercourse, or stress. Most cases resolve gradually within 24 hours with a complete recovery of memory apart from amnesia for the time of the episode. The etiology of transient global amnesia remains a mystery; most people experience only one episode. It is not explained by a transient ischemic episode, seizure activity, or history of migraine headaches. Those who experience transient global amnesia have no greater risk of stroke, transient ischemic attacks, or memory deficits than the general population (Kapur & Wise, 2000).

Emotional memory The amygdala is critical for the processing of emotions (LeDoux, 2000). Recent years have seen a surge of interest in the role of emotion in cognition and memory. Patients with bilateral focal lesions of the amygdala or orbitofrontal cortex consistently show deficits in the perception of facial emotions, appraisal of emotional situations, and ability to predict their outcome (Bechara, Damasio, Damasio, & Anderson, 1994; Morris et al., 1998). These patients also fail to show physiological concomitants of emotion, such as a change in skin conductance response (Glascher & Adolphs, 2003). The close proximity and strong reciprocal connections between the amygdala and the hippocampus are consistent with the tight functional relation between these structures. Thus, it is not surprising that the amygdala plays a role in memory of emotionally laden stimuli. Behavioral studies all point to a contribution of emotion to memory. In neurologically intact individuals, emotional stimuli

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are better remembered than neutral stimuli. In addition, recollection of emotional information is more vivid and generally contains more details. This phenomenon, called emotional memory enhancement, is observed in young adults regardless of the type of stimuli processed (words, short films, or pictures) (Canli, Zhao, Brewer, Gabrieli, & Cahill, 2000; Charles, Mather, & Carstensen, 2003; Kensinger, Brierley, Medford, Growdon, & Corkin, 2002). Emotional memory enhancement is sometimes present in older adults, particularly when stimuli are arousing (Kensinger et al., 2002). In contrast, patients with mild to moderate Alzheimer’s disease do not show emotional memory enhancement (Figure 21.4) (Kensinger, Anderson, Growdon, & Corkin, 2004; Kensinger et al., 2002), presumably because of amygdala atrophy, which can reach 35% even in mild cases (Smith et al., 1999). Recent work has also shown that the difference between young and older individuals may depend on the valence (negative or positive) of the stimuli, with better memory for negative than positive items in young adults, and the opposite pattern in older adults (Charles et al., 2003). Another study, however, did not find this bias in favor of one emotional valence either in young or older participants (Piguet et al., 2004), suggesting that the particular stimuli used may be as important as the age groups. Interestingly, the type of encoding differentially affects subsequent emotional retrieval in young and older adults. Kensinger, Piguet, Krendl, and Corkin (2005) showed groups of young (aged 18–30 years) and older (aged 60–80 years) participants visual scenes that contained a central element that

Figure 21.4 Young and older adults, but not patients with mild Alzheimer’s disease (AD), show significantly better recall for negative and positive words than neutral words (p < .05). Adapted from Kensinger et al. (2002).

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was either neutral or emotional, and a second peripheral element that was always neutral (Figure 21.5). Not surprisingly, young and older adults demonstrated better recognition of the emotional elements than the neutral ones. Both groups also showed better recognition of noncentral (neutral) elements embedded in the neutral scenes compared to the emotional scenes. This result confirmed that the presence of an emotional element tends to interfere with the encoding of the other components of the scene (narrowing of attention). A crucial finding was that the manipulation of encoding instructions reverses this phenomenon, but only in young participants. When warned about a subsequent memory test following the presentation of the scenes, both groups again showed emotional enhancement for the central elements of the scenes. Only the young adults, however, compensated for the narrowing of attention and showed an improvement in their retrieval of peripheral neutral elements embedded in the emotional scenes. This effect was not observed in the older adults. In summary, emotional memory is sensitive to lesions in the orbitofrontal cortex or amygdala. In addition, even in neurologically intact individuals, aspects of emotional memory are dissociable and are differently affected by age-related processes. What is the role of the hippocampus in memory? In 1953, the radical resection of H.M.’s hippocampus and surrounding structures bilaterally for the relief of intractable epilepsy led to the most dramatic discovery in memory research of the twentieth century: it unveiled the importance for memory processing of a seahorse-shaped structure tucked in the MTL region of the brain. Now, 54 years later, the function of the hippocampus remains under debate. Numerous studies have confirmed that bilateral lesions of MTL structures lead to global amnesia, suggesting that

Figure 21.5 The left picture shows a visual scene comprising a central neutral element: the tumbleweed. The right picture shows the visual scene with a central emotional element: the dead cat. Both scenes contain the same peripheral neutral element: the road toward the horizon. Adapted from Kensinger et al., 2005.

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the hippocampus and surrounding cortices play a critical role in transferring information from short-term memory to long-term declarative memory. In addition, the presence of temporally graded retrograde amnesia gives further support for a contribution of this region to the retrieval and consolidation of recently formed memories. The standard model of consolidation (Squire, 1992) posits that, with time, the hippocampus may no longer be essential for the retrieval of the engram from long-term memory. In contrast, proponents of the multiple-trace theory assert that the hippocampus and the MTL region remain necessary throughout life for the retrieval of episodic information (Moscovitch & Nadel, 1998; Nadel & Moscovitch, 1997, 2001; Nadel, Samsonovich, Ryan, & Moscovitch, 2000). Recent findings from a study examining remote autobiographical memory in two amnesic patients gives support to the latter position (Steinvorth, Levine, & Corkin, 2005), as does a recent fMRI study (Steinvorth, Corkin, & Halgren, 2004). Thus, the hippocampus appears to have at least two essential roles. One is to bind recently acquired pieces of information into meaningful, and more permanent, traces; the other is to aid retrieval of information, and to order the information into a sequence of events in time (for a more extensive review on the topic, see Eichenbaum, 2004). In recent years, controversy has surrounded the issue of whether the hippocampus is necessary for the encoding of episodic and semantic information or for episodic information only. This debate followed the report of three patients who sustained hippocampal damage very early in life accompanied by severely impaired memory for day-to-day information, but relatively preserved memory for facts, as demonstrated by preserved language acquisition and normal knowledge acquisition during school-age years (Vargha-Khadem, Gadian, Watkins, Connelly, Van Paesschen, & Mishkin, 1997). The authors suggested that the presence of normal, or near-normal, semantic memory and defective episodic memory in the context of an absent hippocampus supports the view that semantic knowledge may be acquired without the hippocampus, and that the crucial brain areas for this type of information are the entorhinal and perirhinal cortices. According to the traditional model of declarative memory, episodic and semantic memory go hand in hand. The repeated exposure to specific events slowly evolves into an atemporal representation of these events, eventually becoming semantic information. This model stipulates that defective episodic memory is always accompanied by poor semantic memory and that no dissociation between these two systems is possible (Squire & Zola, 1998). In contrast, Tulving (Tulving, 1995; Tulving & Markowitsch, 1998) proposed a different model: the serial parallel independent model, in which declarative memory comprises two independent systems, and episodic encoding is possible only if the semantic system is intact. In other words, episodic memory depends upon the integrity of the semantic memory system, whereas encoding into the semantic system may be done independently of the episodic system. The presence of general knowledge acquisition in very young children in the

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absence of true episodic memory, as well as the recent demonstration of acquisition of semantic knowledge in H.M. (Corkin, 2002; O’Kane, Kensinger, & Corkin, 2004), gives credence to Tulving’s position. Squire and Zola (1998), however, suggested that residual episodic memory was still present in the three patients described by Vargha-Khadem and colleagues, and that their acquisition of semantic knowledge was far from normal. Further, the presence of additional frontal lobe damage in these patients may explain the greater deficit in episodic memory than semantic. Although the specific contributions of neocortical regions (parahippocampal, perirhinal, and entorhinal cortices) to memory processes remain to be fully elucidated, it is evident that the hippocampus plays a critical role in memory. In man, lesions limited to a portion of the hippocampus, the CA1 field, are sufficient to result in a severe amnesia (Oxbury, Oxbury, Renowden, Squier, & Carpenter, 1997; Zola-Morgan, Squire, & Amaral, 1986). In monkeys (Murray, Baxter, & Gaffan, 1998) and rats (Eichenbaum, Dudchenko, Wood, Shapiro, & Tanila, 1999), the hippocampus mediates spatial and nonspatial memory. Recent research with rats suggests that simple sensory associations (e.g. between a smell and a location associated with reward) could be learned despite bilateral lesions to the hippocampal formation (Wood, Agster, & Eichenbaum, 2004). These researchers demonstrated that rats without a hippocampus were just as accurate in remembering a previous odor associated with a reward, as were intact rats. In another experiment, however, only intact rats, and not those with damaged hippocampi, were able to correctly identify the order in which different odors had been presented (Fortin, Agster, & Eichenbaum, 2002). Thus, although not necessary for learning simple associations, the hippocampus is still necessary for rats to encode contextual information, such as time and place. Whether this finding translates to man remains open for debate.

Functional neuroimaging of memory processes Since the early 1990s, an exponential number of studies using functional neuroimaging (fMRI and PET) have attempted to identify the neural substrates of the different components of memory. These techniques measure changes in cerebral blood flow or oxygen concentration in discrete brain areas, either by using weakly radioactive isotopes with a very short half-life (PET), or by detecting magnetic changes associated with variations in blood oxygen level (fMRI). One major advance afforded by functional neuroimaging is that we can now distinguish the neural processes that support encoding of information from those that support retrieval. Functional imaging studies have affirmed the importance of the hippocampus and other MTL areas in memory. The main findings, summarized here, are reviewed extensively in Cabeza and Nyberg (2000) and in Cabeza (2001).

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Encoding processes In young individuals, episodic memory encoding, whether intentional or incidental, results in MTL, PFC, posterior parietal, and cerebellar activation. The MTL activation tends to be lateralized: greater on the left for verbal information and bilateral, or right-sided, for material that is difficult to verbalize (Golby et al., 2001). The PFC region shows a consistent pattern of left-sided activation during verbal tasks (e.g. Kensinger et al., 2003). For visuospatial information, some studies report either right-sided or bilateral activation. Further, the development of event-related designs in fMRI, which allow the detection of change in activation associated with each stimulus rather than the entire task, has uncovered differential activation during encoding for items that are later remembered compared to those that are forgotten (Brewer, Zhao, Desmond, Glover, & Gabrieli, 1998; Paller & Wagner, 2002; Wagner, Koutstaal, & Schacter, 1999; Wagner et al., 1998b). On an incidental memory word task, Wagner and colleagues (1998b) found greater activation at encoding in the left inferior PFC, fusiform gyrus, and MTL for words that were correctly identified during a recognition task than for words that had been forgotten. Thus, it appears that at the time of encoding, activation occurs in different areas when items are later remembered compared to when they are forgotten—the subsequent memory effect. Further, within the MTL, differential activation at the time of encoding in the parahippocampal and perirhinal cortices predicts subsequent source and item recognition, respectively (Davachi, Mitchell, & Wagner, 2003). Retrieval processes During episodic retrieval, consistently greater activation occurs in the right PFC, regardless of the type of information. This activation has been interpreted as reflecting retrieval mode, retrieval effort, or retrieval success (e.g. Buckner et al., 1998; Tulving, 1983; Wagner, Desmond, Glover, & Gabrieli, 1998a). In contrast, activation in the MTL region tends to be more bilateral. In addition, in this region, activation is associated only with retrieval success, and never with retrieval effort or retrieval mode, suggesting that it is related to the level of retrieval performance (successful recollection). Other brain regions show activation during episodic retrieval (e.g. lateral and medial parietal, occipital), highlighting the contributions of posterior association cortices in retrieval of information (Cabeza, Dolcos, Graham, & Nyberg, 2002; Konishi, Wheeler, Donaldson, & Buckner, 2000). Semantic retrieval is also associated with left inferior PFC activation. This activation may reflect the deployment of cognitive control processes during retrieval: control over the selection among competing representations (Thompson-Schill et al., 1998) or over context-relevant information (Badre & Wagner, 2002).

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Working memory Neuroimaging studies have consistently demonstrated increased activity in the PFC during performance of working memory tasks, as in delayed matching to sample and N-back tasks. Ventrolateral and dorsolateral regions within the PFC are selectively activated depending on task requirements (selection, maintenance, or manipulation) (D’Esposito et al., 1999; D’Esposito, Postle, & Rypma, 2000; Petrides, 1996). Studies have also indicated that activation is material dependent: Verbal working memory tasks elicit greater activation in the left than in the right hemisphere while visuospatial working memory tasks elicit the opposite pattern of activation. Further work also indicates that working memory storage (that is, retention of working memory representations) is supported by posterior cortical regions. Activation within these regions is lateralized depending on the stimulus demands (Postle, Druzgal, & D’Esposito, 2003; Postle et al., 2000). Age-related changes Older individuals show patterns of activation that are similar to those seen in young adults on a wide range of tasks, despite increased interindividual variability. Activation, however, tends to be smaller in amplitude and is more likely to be bilateral. For example, on a word-encoding task, young individuals showed activation limited to the posterior frontal region of the left hemisphere, while older adults showed activation in the right posterior frontal region as well (Buckner, 2003). Similar patterns of bilateral activation have also been observed during retrieval tasks (e.g. Grady, Bernstein, Beig, & Siegenthaler, 2002). The meaning of these changes in patterns and levels of activation in aging remains open for debate. The observed underactivation of brain regions appears to reflect an inability of older individuals to spontaneously engage brain regions fully compared to their young counterparts. The recruitment of additional brain regions, which has been labeled “nonselective recruitment”, may indicate a compensatory mechanism to meet task demands accompanied, possibly, by the use of alternative strategies (Cabeza et al., 2004). What remains unclear is whether changes in strategies lead to changes in activation or vice versa. Another view suggests that nonselective recruitment may not be a compensatory mechanism but rather signals a breakdown in appropriate activation, reflecting age-related physiological changes, such as neuronal and white-matter alterations (Logan, Sanders, Snyder, Morris, & Buckner, 2002). Emotional memory Functional neuroimaging studies have confirmed the role of the amygdala in emotional memory processing, with greater amygdalar activation found during recognition of emotional words than neutral words (Tabert et al., 2001),

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and a positive correlation found between left amygdala activation during encoding and subsequent memory of negative emotional scenes (Canli et al., 2000). Kensinger and Corkin (2004) further described two circuits for encoding negative, nonarousing and arousing words, respectively, compared to neutral items. Emotionally arousing items (taboo words) evoked greater activation in an amygdalar-hippocampal circuit, whereas greater activation was present in a prefrontal-hippocampal circuit for emotional but nonarousing items. The introduction of a secondary working memory task interfered with performance on the emotional nonarousing items, whereas performance on the emotional arousing items remained unchanged. This finding delineates the cognitive processes that support the emotional memory enhancement effect. The concurrent and correlated activation of the hippocampus and amygdala during the processing of arousing information appears to occur automatically, leading to better memory for arousing items. In contrast, activation of a prefrontal-hippocampal circuit probably reflects engagement of attentiondemanding, cognitive control processes (semantic or autobiographical elaboration) that enhance encoding of negative but nonarousing information (Kensinger & Corkin, 2004).

Comment During the past 50 years, our knowledge of memory and disorders of memory has grown tremendously. This progress is due to advances in three interrelated domains: theory, technology, and clinical acumen. Theoretical models of memory have been postulated in part by cognitive scientists, and in part on the basis of clinical information, such as seminal single-case and group studies. Then, proposed models have been tested in intact and clinical populations. Advances in technology go hand in hand with this dual interaction. For example, the greater availability of functional neuroimaging has allowed researchers to ask questions about aspects of memory processes that were not previously possible in the study of brain-lesioned patients. Good questions yield interesting responses that challenge, confirm, or disprove existing models and expand knowledge further. Numerous good questions have been asked and some have received partial answers. Now, we know more about why some events are remembered while others are not. We know more about memory encoding and retrieval processes, and about the role of emotions, aging, and various neuropathological changes in these processes. We know more about different kinds of memory and their unique aspects. Nevertheless, many questions about memory function remain unanswered or only partly answered, and some are yet to be fully formulated. There is no doubt, however, that memory research is in a healthy state, as reflected by the vigorous debates surrounding some issues: for example, the role of the hippocampus in long-term memory retrieval and in autobiographical memory, and the contribution of the dorsolateral and left inferior PFC to memory processes. The functional relations among brain structures during performance

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of memory tasks also remain to be characterized. Mechanisms and location of very long-term memory storage also demand further investigation. Another major challenge for the future is to understand the relation between the kind of cognitive and neural processes described in this chapter and their molecular and cellular basis (Bailey, Kandel, & Si, 2004; Wiltgen, Brown, Talton, & Silva, 2004). Even in the face of these changes, it is tempting to speculate that future discoveries resulting from interdisciplinary efforts will finally lead to robust treatments for memory disorders.

Acknowledgment Olivier Piguet is supported by a National Health and Medical Research Council of Australia Neil Hamilton Fairley postdoctoral fellowship (no. 222909).

References Alexander, M. P., & Freedman, M. (1984). Amnesia after anterior communicating artery aneurysm rupture. Neurology, 34, 752–757. Baddeley, A. (1998). The central executive: A concept and some misconceptions. Journal of the International Neuropsychological Society, 4, 523–526. Baddeley, A. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4, 417–423. Baddeley, A. D. (1986). Working memory. London: Oxford University Press. Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. A. Bower (Ed.), The psychology of learning and motivation (pp. 47–89). New York: Academic Press. Badre, D., & Wagner, A. D. (2002). Semantic retrieval, mnemonic control, and prefrontal cortex. Behavioral and Cognitive Neurosciences Reviews, 1, 206–218. Bailey, C. H., Kandel, E. R., & Si, K. (2004). The persistence of long-term memory: A molecular approach to self-sustaining changes in learning-induced synaptic growth. Neuron, 44, 49–57. Bayley, J. (1999). Elegy for Iris. New York: Picador. Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 7–15. Bondi, M. W., Kaszniak, A. W., Rapcsak, S. Z., & Butters, M. A. (1993). Implicit and explicit memory following anterior communicating artery aneurysm rupture. Brain and Cognition, 22, 213–229. Braak, H., Braak, E., Yilmazer, D., de Vos, R. A., Jansen, E. N., & Bohl, J. (1996). Pattern of brain destruction in Parkinson’s and Alzheimer’s diseases. Journal of Neural Transmission, 103, 455–490. Braver, T. S., Cohen, J. D., & Barch, D. M. (2001). The role of prefrontal cortex in normal and disordered cognitive control: A cognitive neuroscience perspective. In D. Stuss & R. T. Knight (Eds.), Principles of frontal lobe function (pp. 422–448). Oxford: Oxford University Press. Brewer, J. B., Zhao, Z., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (1998). Making memories: Brain activity that predicts how well visual experience will be remembered. Science, 281, 1185–1187.

430

Piguet and Corkin

Buckner, R. L. (2003). Functional-anatomic correlates of control processes in memory. Journal of Neuroscience, 23, 3999–4004. Buckner, R. L., Koutstaal, W., Schacter, D. L., Dale, A. M., Rotte, M., & Rosen, B. R. (1998). Functional-anatomic study of episodic retrieval. II. Selective averaging of event-related fMRI trials to test the retrieval success hypothesis. NeuroImage, 7, 163–175. Butters, N. (1985). Alcoholic Korsakoff’s syndrome: Some unresolved issues concerning etiology, neuropathology, and cognitive deficits. Journal of Clinical and Experimental Neuropsychology, 7, 181–210. Butters, N., & Cermak, L. S. (1980). Alcoholic Korsakoff’s syndrome: An information processing approach to amnesia. New York: Academic Press. Cabeza, R. (2001). Cognitive neuroscience of aging: Contributions of functional neuroimaging. Scandinavian Journal of Psychology, 42, 277–286. Cabeza, R., Daselaar, S. M., Dolcos, F., Prince, S. E., Budde, M., & Nyberg, L. (2004). Task-independent and task-specific age effects on brain activity during working memory, visual attention and episodic retrieval. Cerebral Cortex, 14, 364–375. Cabeza, R., Dolcos, F., Graham, R., & Nyberg, L. (2002). Similarities and differences in the neural correlates of episodic memory retrieval and working memory. NeuroImage, 16, 317–330. Cabeza, R., & Nyberg, L. (2000). Imaging cognition. II. An empirical review of 275 PET and fMRI studies. Journal of Cognitive Neuroscience, 12, 1–47. Canli, T., Zhao, Z., Brewer, J., Gabrieli, J. D., & Cahill, L. (2000). Event-related activation in the human amygdala associates with later memory for individual emotional experience. Journal of Neuroscience, 20 (RC99), 1–5. Charles, S. T., Mather, M., & Carstensen, L. L. (2003). Aging and emotional memory: The forgettable nature of negative images for older adults. Journal of Experimental Psychology: General, 132, 310–324. Cohen, N. J., & Squire, L. R. (1980). Preserved learning and retention of patternanalyzing skill in amnesia: Dissociation of knowing how and knowing that. Science, 210, 207–209. Corkin, S. (1984). Lasting consequences of bilateral medial temporal lobectomy: Clinical course and experimental findings in H.M. Seminars in Neurology, 4, 252–262. Corkin, S. (2002). What’s new with the amnesic patient H.M.? Nature Reviews. Neuroscience, 3, 153–160. Corkin, S., Amaral, D. G., Gonzalez, R. G., Johnson, K. A., & Hyman, B. T. (1997). H.M.’s medial temporal lobe lesion: Findings from magnetic resonance imaging. Journal of Neuroscience, 17, 3964–3979. Corkin, S., Cohen, N. J., Sullivan, E. V., Clegg, R. A., Rosen, T. J., & Ackerman, R. H. (1985). Analyses of global memory impairment of different etiologies. In D. S. Olton, E. Gamzu, & S. Corkin (Eds.), Memory dysfunctions. Volume 444: An integration of animal and human research from preclinical and clinical perspectives (pp. 10–40). New York: Annals of the New York Academy of Sciences. Craik, F. I. M. (1986). A functional account of age differences in memory. In F. Klix & H. Hagendord (Eds.), Human memory and cognitive capabilities: Mechanisms and performances (pp. 409–422). Amsterdam: Elsevier. Cullen, K. M., Halliday, G. M., Caine, D., & Kril, J. J. (1997). The nucleus basalis (Ch4) in the alcoholic Wernicke–Korsakoff syndrome: Reduced cell number in

21. Memory: structure, function, and dysfunction

431

both amnesic and non-amnesic patients. Journal of Neurology, Neurosurgery, and Psychiatry, 63, 315–320. Damasio, H. C. (1991). Neuroanatomy of frontal lobe in vivo: A comment on methodology. In H. S. Levin, H. M. Eisenberg, & A. L. Benton (Eds.), Frontal lobe function and dysfunction (pp. 92–129). New York: Oxford University Press. Davachi, L., Mitchell, J. P., & Wagner, A. D. (2003). Multiple routes to memory: Distinct medial temporal lobe processes build item and source memories. Proceedings of the National Academy of Sciences of the USA, 100, 2157–2162. Demery, J. A., Hanlon, R. E., & Bauer, R. M. (2001). Profound amnesia and confabulation following traumatic brain injury. Neurocase, 7, 295–302. D’Esposito, M., Alexander, M. P., Fischer, R., McGlinchey-Berroth, R., & O’Connor, M. (1996). Recovery of memory and executive function following anterior communicating artery aneurysm rupture. Journal of the International Neuropsychological Society, 2, 565–570. D’Esposito, M., Postle, B. R., Ballard, D., & Lease, J. (1999). Maintenance versus manipulation of information held in working memory: An event-related fMRI study. Brain and Cognition, 41, 66–86. D’Esposito, M., Postle, B. R., & Rypma, B. (2000). Prefrontal cortical contributions to working memory: Evidence from event-related fMRI studies. Experimental Brain Research, 133, 3–11. Dobbins, I. G., Rice, H. J., Wagner, A. D., & Schacter, D. L. (2003). Memory orientation and success: Separable neurocognitive components underlying episodic recognition. Neuropsychologia, 41, 318–333. Double, K. L., Halliday, G. M., Kril, J. J., Harasty, J. A., Cullen, K., Brooks, W. S., et al. (1996). Topography of brain atrophy during normal aging and Alzheimer’s disease. Neurobiology of Aging, 17, 513–521. Ebbinghaus, H. (1885/1913). Memory: A contribution to experimental psychology. New York: Teachers College, Columbia University. Eichenbaum, H. (2004). Hippocampus: Cognitive processes and neural representations that underlie declarative memory. Neuron, 44, 109–120. Eichenbaum, H., Dudchenko, P., Wood, E., Shapiro, M., & Tanila, H. (1999). The hippocampus, memory, and place cells: Is it spatial memory or a memory space? Neuron, 23, 209–226. Fama, R., Marsh, L., & Sullivan, E. V. (2004). Dissociation of remote and anterograde memory impairment and neural correlates in alcoholic Korsakoff syndrome. Journal of the International Neuropsychological Society, 10, 427–441. Fortin, N. J., Agster, K. L., & Eichenbaum, H. B. (2002). Critical role of the hippocampus in memory for sequences of events. Nature Neuroscience, 5, 458–462. Fortin, N. J., Wright, S. P., & Eichenbaum, H. (2004). Recollection-like memory retrieval in rats is dependent on the hippocampus. Nature, 431, 188–191. Fuster, J. M. (2001). The prefrontal cortex–an update: Time is of the essence. Neuron, 30, 319–333. Glascher, J., & Adolphs, R. (2003). Processing of the arousal of subliminal and supraliminal emotional stimuli by the human amygdala. Journal of Neuroscience, 23, 10274–10282. Glisky, E. L., Rubin, S. R., & Davidson, P. S. (2001). Source memory in older adults: An encoding or retrieval problem? Journal of Experimental Psychology: Learning, Memory, and Cognition, 27, 1131–1146. Golby, A. J., Poldrack, R. A., Brewer, J. B., Spencer, D., Desmond, J. E., Aron, A. P.,

432

Piguet and Corkin

et al. (2001). Material-specific lateralization in the medial temporal lobe and prefrontal cortex during memory encoding. Brain, 124, 1841–1854. Goldman-Rakic, P. S. (1987). Circuitry of the prefrontal cortex and the regulation of behavior by representational memory. In V. B. Mountcastle, F. Plum, & S. R. Geiger (Eds.), Handbook of neurobiology (pp. 373–417). Bethesda, MD: American Physiological Society. Grady, C. L., Bernstein, L. J., Beig, S., & Siegenthaler, A. L. (2002). The effects of encoding strategy on age-related changes in the functional neuroanatomy of face memory. Psychology and Aging, 17, 7–23. Graff-Radford, N. R., Tranel, D., Hoesen, G. V., & Brandt, J. (1990). Diencephalic amnesia. Brain, 113, 1–25. Grafman, J., Salazar, A. M., Weingartner, H., Vance, S. C., & Ludlow, C. (1985). Isolated impairment of memory following a penetrating lesion of the fornix cerebri. Archives of Neurology, 42, 1162–1168. Hodges, J. R., & Patterson, K. E. (1997). Semantic memory disorders. Trends in Cognitive Sciences, 1, 68. Insausti, A., & Amaral, D. G. (2004). Hippocampal formation. In G. Paxinos & J. K. Mai (Eds.), The human nervous system (2nd ed., pp. 871–914). Amsterdam: Elsevier. James, W. (1890). The principles of psychology (vol. 1). New York: Henry Holt. Janowsky, J. S., Shimamura, A. P., & Squire, L. R. (1989). Source memory impairment in patients with frontal lobe lesions. Neuropsychologia, 27, 1043–1056. Josse, G., & Tzourio-Mazoyer, N. (2004). Hemispheric specialization for language. Brain Research Reviews, 44, 1–12. Kapur, N., & Wise, R. J. (2000). Transient and reversible memory disorders in neurological disease. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology (2nd ed., pp. 133–154). Amsterdam: Elsevier. Kensinger, E. A., Anderson, A., Growdon, J. H., & Corkin, S. (2004). Effects of Alzheimer disease on memory for verbal emotional information. Neuropsychologia, 42, 791–800. Kensinger, E. A., Brierley, B., Medford, N., Growdon, J. H., & Corkin, S. (2002). Effects of normal aging and Alzheimer’s disease on emotional memory. Emotion, 2, 118–134. Kensinger, E. A., Clarke, R. J., & Corkin, S. (2003). What neural correlates underlie successful encoding and retrieval? A functional magnetic resonance imaging study using a divided attention paradigm. Journal of Neuroscience, 23, 2407–2415. Kensinger, E. A., & Corkin, S. (2004). Two routes to emotional memory: distinct neural processes for valence and arousal. Proceedings of the National Academy of Sciences of the USA, 101, 3310–3315. Kensinger, E. A., Piguet, O., Krendl, A. C., & Corkin, S. (2005). Memory for contextual details: Effects of emotion and aging. Psychology and Aging, 20, 241–250. Knuttinen, M. G., Power, J. M., Preston, A. R., & Disterhoft, J. F. (2001). Awareness in classical differential eyeblink conditioning in young and aging humans. Behavioral Neuroscience, 115, 747–757. Konishi, S., Wheeler, M. E., Donaldson, D. I., & Buckner, R. L. (2000). Neural correlates of episodic retrieval success. NeuroImage, 12, 276–286. LeDoux, J. E. (2000). Emotion circuits in the brain. Annual Review of Neuroscience, 23, 155–184. Locascio, J. J., Growdon, J. H., & Corkin, S. (1995). Cognitive test performance in

21. Memory: structure, function, and dysfunction

433

detecting, staging, and tracking Alzheimer’s disease. Archives of Neurology, 52, 1087–1099. Logan, J. M., Sanders, A. L., Snyder, A. Z., Morris, J. C., & Buckner, R. L. (2002). Under-recruitment and nonselective recruitment: Dissociable neural mechanisms associated with aging. Neuron, 33, 827–840. Mair, W. G., Warrington, E. K., & Weiskrantz, L. (1979). Memory disorder in Korsakoff’s psychosis: A neuropathological and neuropsychological investigation of two cases. Brain, 102, 749–783. Malamut, B. L., Graff-Radford, N., Chawluk, J., Grossman, R. I., & Gur, R. C. (1992). Memory in a case of bilateral thalamic infarction. Neurology, 42, 163–169. Markowitsch, H. J., von Cramon, D. Y., & Schuri, U. (1993). Mnestic performance profile of a bilateral diencephalic infarct patient with preserved intelligence and severe amnesic disturbances. Journal of Clinical and Experimental Neuropsychology, 15, 627–652. Mattioli, F., Miozzo, A., & Vignolo, L. A. (1999). Confabulation and delusional misidentification: A four year follow-up study. Cortex, 35, 413–422. Mesulam, M., Shaw, P., Mash, D., & Weintraub, S. (2004). Cholinergic nucleus basalis tauopathy emerges early in the aging-MCI-AD continuum. Annals of Neurology, 55, 815–828. Milner, B. (1971). Interhemispheric differences in the localization of psychological processes in man. British Medical Bulletin, 27, 272–277. Milner, B. (1978). Clues to the cerebral organization of memory. In P. Buser & A. Rougeul-Buser (Eds.), Cerebral correlates of conscious experience (pp. 139–153). Amsterdam: Elsevier. Milner, B. (1985). Memory and the human brain. In M. Shafto (Ed.), How we know (pp. 31–59). San Francisco: Harper & Row. Milner, B., Petrides, M., & Smith, M. L. (1985). Frontal lobes and the temporal organization of memory. Human Neurobiology, 4, 137–142. Morris, J. S., Friston, K. J., Büchel, C., Frith, C. D., Young, A. W., Calder, A. J., et al. (1998). A neuromodulatory role for the human amygdala in processing emotional facial expressions. Brain, 121, 47–57. Moscovitch, M., & Nadel, L. (1998). Consolidation and the hippocampal complex revisited: In defense of the multiple-trace model. Current Opinion in Neurobiology, 8, 297–300. Moscovitch, M., & Winocur, G. (2002). The frontal cortex and working with memory. In D. T. Stuss & R. T. Knight (Eds.), Principles of frontal lobe function (pp. 188–209). New York: Oxford University Press. Murray, E. A., Baxter, M. G., & Gaffan, D. (1998). Monkeys with rhinal cortex damage or neurotoxic hippocampal lesions are impaired on spatial scene learning and object reversals. Behavioral Neuroscience, 112, 1291–1303. Nadel, L., & Moscovitch, M. (1997). Memory consolidation, retrograde amnesia and the hippocampal complex. Current Opinion in Neurobiology, 7, 217–227. Nadel, L., & Moscovitch, M. (2001). The hippocampal complex and long-term memory revisited. Trends in Cognitive Sciences, 5, 228–230. Nadel, L., Samsonovich, A., Ryan, L., & Moscovitch, M. (2000). Multiple trace theory of human memory: Computational, neuroimaging, and neuropsychological results. Hippocampus, 10, 352–368. O’Kane, G., Kensinger, E. A., & Corkin, S. (2004). Evidence for semantic learning in profound amnesia: An investigation with patient H.M. Hippocampus, 14, 417–425.

434

Piguet and Corkin

Owen, A. M., Evans, A. C., & Petrides, M. (1996). Evidence for a two-stage model of spatial working memory processing within the lateral frontal cortex: A positron emission tomography study. Cerebral Cortex, 6, 31–38. Oxbury, S., Oxbury, J., Renowden, S., Squier, W., & Carpenter, K. (1997). Severe amnesia: An unusual late complication after temporal lobectomy. Neuropsychologia, 35, 975–988. Paller, K. A., & Wagner, A. D. (2002). Observing the transformation of experience into memory. Trends in Cognitive Sciences, 6, 93–102. Pantoni, L., Lamassa, M., & Inzitari, D. (2000). Transient global amnesia: A review emphasizing pathogenic aspects. Acta Neurologica Scandinavica, 102, 275–283. Perl, T. M., Bedard, L., Kosatsky, T., Hockin, J. C., Todd, E. C., & Remis, R. S. (1990). An outbreak of toxic encephalopathy caused by eating mussels contaminated with domoic acid. New England Journal of Medicine, 322, 1775—1780. Petrides, M. (1987). Conditional learning and the primate frontal cortex. In E. Perecman (Ed.), The frontal lobes revisited (pp. 91–108). New York: IRBN Press. Petrides, M. (1991). Monitoring of selections of visual stimuli and the primate frontal cortex. Proceedings of the Royal Society of London. Series B, Biological Sciences, 246, 293–298. Petrides, M. (1994). Frontal lobes and working memory: Evidence from investigations of the effects of cortical excisions in nonhuman primates. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology (pp. 59–82). Amsterdam: Elsevier. Petrides, M. (1996). Lateral frontal cortical contribution to memory. Seminars in Neuroscience, 8, 57–63. Petrides, M., Alivisatos, B., Meyer, E., & Evans, A. C. (1993). Functional activation of the human frontal cortex during the performance of verbal working memory tasks. Proceedings of the National Academy of Sciences of the USA, 90, 878–882. Petrides, M., & Milner, B. (1982). Deficits on subject-oriented tasks after frontal- and temporal-lobe lesions in man. Neuropsychologia, 20, 249–262. Piguet, O., Krendl, A. C., Prince, K., & Corkin, S. (2004). Emotional memory in aging: Effect of delay on recognition. Program No. 549.21. 2004 Abstract Viewer/Itinerary Planner. Washington, DC: Society for Neuroscience. Poldrack, R. A., & Wagner, A. D. (2004). What can neuroimaging tell us about the mind? Current Directions in Psychological Science, 13, 177–181. Postle, B. R., Druzgal, T. J., & D’Esposito, M. (2003). Seeking the neural substrates of visual working memory storage. Cortex, 39, 927–946. Postle, B. R., Stern, C. E., Rosen, B. R., & Corkin, S. (2000). An fMRI investigation of cortical contributions to spatial and nonspatial visual working memory. NeuroImage, 11, 409–423. Rao, S. C., Rainer, G., & Miller, E. K. (1997). Integration of what and where in the primate prefrontal cortex. Science, 276, 821–824. Ribot, T. (1881). Les Maladies de la mémoire [Diseases of memory]. Paris: Germer Baillière. Rinne, J. O., Paljarvi, L., & Rinne, U. K. (1987). Neuronal size and density in the nucleus basalis of Meynert in Alzheimer’s disease. Journal of Neurological Science, 79, 67–76. Rugg, M. D., Henson, R. N. A., & Robb, W. G. K. (2003). Neural correlates of retrieval processing in the prefrontal cortex during recognition and exclusion tasks. Neuropsychologia, 41, 40–52.

21. Memory: structure, function, and dysfunction

435

Runes, D. D. (Ed.). (1948). The diary and sundry observations of Thomas Alva Edison. New York: Philosophical Library. Salat, D. H., Kaye, J. A., & Janowsky, J. S. (1999). Prefrontal gray and white matter volumes in healthy aging and Alzheimer disease. Archives of Neurology, 56, 338–344. Scoville, W. B., & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions. Journal of Neurology, Neurosurgery, and Psychiatry, 20, 11–21. Shimamura, A., Janowsky, J. S., & Squire, L. R. (1990). Memory for the temporal order of events in patients with frontal lobe lesions and amnesic patients. Neuropsychologia, 28, 803–813. Smith, C. D., Malcein, M., Meurer, K., Schmitt, F. A., Markesbery, W. R., & Pettigrew, L. C. (1999). MRI temporal lobe volume measures and neuropsychologic function in Alzheimer’s disease. Journal of NeuroImaging, 9, 2–9. Squire, L., Amaral, D., Zola-Morgan, S., Kritchevsky, M., & Press, G. (1989). Description of brain injury in the amnesic patient N.A. based on magnetic resonance imaging. Experimental Neurology, 105, 23–25. Squire, L. R. (1992). Memory and the hippocampus: A synthesis from findings with rats, monkeys, and humans. Psychological Review, 99, 195–231. Squire, L. R., & Zola, S. M. (1996). Ischemic brain damage and memory impairment: A commentary. Hippocampus, 6, 546–552. Squire, L. R., & Zola, S. M. (1998). Episodic memory, semantic memory, and amnesia. Hippocampus, 8, 205–211. Steinvorth, S., Corkin, S., & Halgren, E. (2004). fMRI evidence that medial temporal lobe (MTL) structures support retrieval of old autobiographical memories. Program No. 596.11, 2004 Abstract Viewer/Itinerary Planner. Washington, DC: Society for Neuroscience. Steinvorth, S., Levine, B., & Corkin, S. (2005). Medial temporal lobe structures are needed to re-experience remote autobiographical memories. Neuropsychologia, 43, 479–496. Suzuki, W. A., & Eichenbaum, H. (2000). The neurophysiology of memory. Annals of the New York Academy of Sciences, 911, 175–191. Tabert, M. H., Borod, J. C., Tang, C. Y., Lange, G., Wei, T. C., Johnson, R., et al. (2001). Differential amygdala activation during emotional decision and recognition memory tasks using unpleasant words: An fMRI study. Neuropsychologia, 39, 556–573. Thompson-Schill, S. L., D’Esposito, M., Aguirre, G. K., & Farah, M. J. (1997). Role of left inferior prefrontal cortex in retrieval of semantic knowledge: A reevaluation. Proceedings of the National Academy of Sciences of the USA, 94, 14792–14797. Thompson-Schill, S. L., Swick, D., Farah, M. J., D’Esposito, M., Kan, I. P., & Knight, R. T. (1998). Verb generation in patients with focal frontal lesions: A neuropsychological test of neuroimaging findings. Proceedings of the National Academy of Sciences of the USA, 95, 15855–15860. Tranel, D., Damasio, H., & Damasio, A. R. (2000). Amnesia caused by herpes simplex encephalitis, infarctions in basal forebrain, and anoxia/ischemia. In L. S. Cermak (Ed.), Handbook of neuropsychology (2nd ed., pp. 85–110). Amsterdam: Elsevier. Tulving, E. (1972). Episodic and semantic memory. In E. Tulving & W. Donaldson (Eds.), Organization of memory (pp. 381–403). New York: Academic Press. Tulving, E. (1983). Elements of episodic memory. Oxford: Clarendon. Tulving, E. (1995). Organization of memory: Quo vadis? In M. S. Gazzaniga (Ed.), The cognitive neurosciences (pp. 839–847). Cambridge, MA: MIT Press.

436

Piguet and Corkin

Tulving, E. (2002). Episodic memory: From mind to brain. Annual Review of Psychology, 53, 1–25. Tulving, E., & Markowitsch, H. J. (1998). Episodic and declarative memory: Role of the hippocampus. Hippocampus, 8, 198–204. Vargha-Khadem, F., Gadian, D. G., Watkins, K. E., Connelly, A., Van Paesschen, W., & Mishkin, M. (1997). Differential effects of early hippocampal pathology on episodic and semantic memory. Science, 277, 376–380. Visser, P. J., Krabbendam, L., Verhey, F. R. J., Hofman, P. A. M., Verhoeven, W. M. A., Tuinier, S., et al. (1999). Brain correlates of memory dysfunction in alcoholic Korsakoff’s syndrome. Journal of Neurology, Neurosurgery, and Psychiatry, 67, 774–778. Wagner, A. D., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (1998a). Prefrontal cortex and recognition memory. Functional-MRI evidence for context-dependent retrieval processes. Brain, 121, 1985–2002. Wagner, A. D., Koutstaal, W., & Schacter, D. L. (1999). When encoding yields remembering: Insights from event-related neuroimaging. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 354, 1307–1324. Wagner, A. D., et al. (1998b). Building memories: Remembering and forgetting of verbal experiences as predicted by brain activity. Science, 281, 1188–1191. Warrington, E. K., & Weiskrantz, L. (1982). Amnesia: A disconnection syndrome? Neuropsychologia, 20, 233–248. West, R., Jakubek, K., & Wymbs, N. (2002). Age-related declines in prospective memory: Behavioral and electrophysiological evidence. Neuroscience and Biobehavioral Reviews, 26, 827–833. Wickelgren, W. A. (1968). Sparing of short-term memory in an amnesic patient: Implications for strength theory of memory. Neuropsychologia, 6, 235–244. Wilson, B. A., Baddeley, A. D., & Kapur, N. (1995). Dense amnesia in a professional musician following herpes simplex virus encephalitis. Journal of Clinical and Experimental Neuropsychology, 17, 668–681. Wilson, F. A. W., Scalaidhe, S. P., & Goldman-Rakic, P. S. (1993). Dissociation of object and spatial processing domains in primate prefrontal cortex. Science, 260, 1955–1958. Wiltgen, B. J., Brown, R. A., Talton, L. E., & Silva, A. J. (2004). New circuits for old memories: The role of the neocortex in consolidation. Neuron, 44, 101–108. Winocur, G., Oxbury, S., Roberts, R., Agnetti, V., & Davis, C. (1984). Amnesia in a patient with bilateral lesions to the thalamus. Neuropsychologia, 22, 123–143. Wood, E. R., Agster, K. M., & Eichenbaum, H. (2004). One-trial odor-reward association: A form of event memory not dependent on hippocampal function. Behavioral Neuroscience, 118, 526–539. Woodruff-Pak, D. S., Goldenberg, G., Downey-Lamb, M. M., Boyko, O. B., & Lemieux, S. K. (2000). Cerebellar volume in humans related to magnitude of classical conditioning. Neuroreport, 11, 609–615. Yoneoka, Y., Takeda, N., Inoue, A., Ibuchi, Y., Kumagai, T., Sugai, T., et al. (2004). Acute Korsakoff syndrome following mammillothalamic tract infarction. American Journal of Neuroradiology, 25, 964–968. Zola-Morgan, S., Squire, L. R., & Amaral, D. G. (1986). Human amnesia and the medial temporal region: Enduring memory impairment following a bilateral lesion limited to field CA1 of the hippocampus. Journal of Neuroscience, 6, 2950–2967.

22 Effects of aging and dementia on memory1 Gianfranco Dalla Barba, François Boller, and Dorothée Rieu

Memory, memory systems, and subsystems Historical It is well established that memory is not a unitary system. This idea has a long and rich history. For example, the distinction between knowing and remembering, that is, between knowledge and memory, can be traced back to ancient Greek philosophers, including Aristotle. In more recent times, the hypothesis that the acquisition and retrieval of different kinds of information depend on distinct mechanisms characterized by different properties has been articulated by several philosophers and scientists, including Bergson (1896), Gall (1835), Maine de Biran (1804, trans. 1929), James (1890), Ribot (1882), Claparède (1911), Korsakoff (1889), Husserl (1950), and Sartre (1943) among others. After World War II, a number of hypotheses concerning multiple forms of memory were put forward. A key breakthrough in this issue is due to what can truly be called an accident. William Scoville, a neurosurgeon, and Brenda Milner, a neuropsychologist, described the case of a young man, known by the initials H.M., who had undergone a complete bilateral resection of the medial temporal lobes for relief of intractable epilepsy (Scoville & Milner, 1957). H.M. showed severe anterograde and retrograde amnesia, even though his overall level of intelligence remained above average and other cognitive functions were unaffected. A few years later, Warrington and Weiskrantz (1968) showed that amnesic patients can learn implicitly information that they cannot recall explicitly, that is, on a conscious basis. This implicit form of learning, known since then as the priming effect, led to an explosion of experimental studies in the following decades. However, although many theoretical and empirical dissociations within memory have been proposed for many centuries, the notion that memory is organized in different systems is quite recent and can be traced back to the distinction between episodic and semantic memory proposed by Tulving in 1972.

438 Dalla Barba, Boller, Rieu What a system is not The aim of this chapter is to critically review the differential impact of aging and dementia on memory systems and subsystems. Because of the confusion existing in the literature, it is essential to state first what a memory system is not. Forms or kinds of memory and memory systems are not equivalent concepts. As pointed out by Schacter and Tulving (1994), the latter includes the former, but the former does not necessarily include the latter. For example, verbal memory, spatial memory, olfactory memory, and recognition memory are different forms of memory and they can help to organize empirical facts, but they do not constitute memory systems. The same can be said for processes, tasks, and expression of memory. In short, memory systems include different forms of memory, and processes, tasks, and modes of expression of memory, but they do not coincide with them. So, the next question is, “What is a memory system supposed to be?” Definition of memory systems In an early formulation, Tulving (1984a) proposed that different memory systems are distinguished in terms of: 1 2 3 4 5

different behaviour and cognitive functions and the kind of information and knowledge they process operations according to different laws and principles different neural substrates (neural structures and neural mechanisms) differences in the timing of their appearance in phylogenetic and ontogenetic development differences in the format of represented information (the extent to which the aftereffects of information acquisition represent the past or merely modify future behavior or experience).

A memory system differs from other memory systems in its neural mechanisms, the kind of information it processes, and the rules and laws of its operation. This definition of a memory system was rephrased by Sherry and Schacter (1987), who proposed that different memory systems evolve as special adaptations of information storage and retrieval for specific and functionally incompatible purposes. They defined a memory system as “an interaction among acquisition, retention and retrieval mechanisms that is characterized by certain rules of operation” (p. 440), and suggested that the term “multiple memory system” “refers to the idea that two or more systems are characterized by fundamentally different rules of operation” (p. 440). Specific criteria for postulating the existence of a particular memory system are proposed by Schacter and Tulving (1994), but their discussion goes beyond the aims of this chapter. It must be emphasized, however, that although much still needs to be learned about memory systems, a considerable

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amount of converging evidence from the neuropsychological literature clearly indicates that it is reasonable to postulate the existence of different memory systems. In this chapter, we will follow the classification proposed by Schacter and Tulving (1994), which includes the five major systems of human memory reported in Table 22.1.

Procedural memory The first major system is procedural memory. It includes a vast category of probably heterogeneous and largely unknown phenomena. Thus, defining procedural memory is quite difficult and only a general, tentative definition may be attempted. In very broad terms, procedural memory can be defined as a memory system that is not accessible in terms of specific facts, data, or spatiotemporally determined events. Procedural memory is the kind of memory involved in learning skills and other cognitively modifiable operations. This definition, though imprecise, nevertheless underscores that procedural memory operates outside consciousness, is automatic and not consciously controlled, and lacks flexibility. It is characterized by gradual, incremental learning and appears to be especially well suited for picking up and dealing with invariant aspects of the environment over time (Sherry & Schacter, 1987). Because of the lack of information concerning procedural memory, this memory system was originally defined negatively: procedural memory was considered a nondeclarative form of memory, a collection of nonconscious memory abilities, all of which are intact in otherwise severely amnesic patients (Squire, 1987), and it was contrasted with declarative memory, a collection of conscious memory abilities, all of which are considered to be Table 22.1

Classification of memory systems

System

Other terms

Subsystems

Retrieval

1. Procedural

Nondeclarative

Implicit

2. Perceptual representation system (PRS) 3. Semantic

Nondeclarative

Motor skills Cognitive skills Simple conditioning Simple associative learning Visual word form Auditory word form Structural description Spatial Relational

4. Primary 5. Episodic

Generic Factual Knowledge Working Short-term Personal Autobiographical Event memory

Visual Auditory

Implicit

Implicit

Explicit Explicit

440 Dalla Barba, Boller, Rieu impaired in severely amnesic patients (Cohen & Squire, 1980). However, more recent work has shown that procedural memory is not the only memory system that operates on an unconscious basis, and that it is not the only memory system preserved in severe amnesia. As we will see later on, the perceptual representation system (PRS) also operates on an unconscious basis, and it is quite resistant to brain disorder as in amnesia and various forms of dementia. Furthermore, as may be gathered from Table 22.1, a number of subsystems are now considered to be part of procedural memory, namely motor skill learning, nonmotor (or cognitive) skill learning, classic Pavlovian simple conditioning, and simple associative learning. Why are all these memory subsystems grouped under the label of procedural memory? The answer is still incomplete but, again, is derived by subtraction. It is incomplete because we do not know exactly which neural and cognitive resources these subsystems share. It derives by subtraction because evidence in favor of the existence of the PRS limits, as we will see, the domain of procedural memory to the cognitive operations that are not strongly perceptually based. Aging Studies on “normal” aging pose considerable methodological and theoretical problems (Gabrieli, 1993). Cross-sectional studies examining the impact of aging on memory performance are susceptible to confounding cohort effects (differences between the groups of different ages that are not due to aging itself). In fact, longitudinal studies have shown that declines in cognitive functions are considerably smaller than indicated by cross-sectional studies (Schaie & Labouvie-Vief, 1974). However, apart from this caveat, which applies to all the studies on normal aging reported in this chapter, the literature does not provide any information on the impact of normal aging on procedural memory performance. Several studies, as we will see later, have dealt with the effect of aging on various kinds of priming. Other studies have compared priming, motor skill learning, and cognitive skill learning in normal aging and various neurological diseases. However, to our knowledge, the question of whether procedural memory, as defined in the classification reported above (motor skills learning, cognitive skills, simple conditioning, and simple associative learning), may be influenced by aging, has never been experimentally addressed. There is some evidence that procedural memory, or at least some aspects or subsystems of procedural memory, is subserved by the corticostriatal system (Mishkin, Malamut, & Bachevalier, 1984). The corticostriatal system is known to be less affected by aging than the corticolimbic system. This would tentatively explain why, at least anecdotally, elderly subjects do not show or complain about skill learning and other procedural memory impairments, while they often show and complain of their explicit memory performances.

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Alzheimer’s disease (AD) In AD patients, skill learning, both of motor and cognitive skills, is relatively preserved in comparison to explicit learning. The first demonstration that AD patients can learn a motor skill in a normal manner was provided by Eslinger and Damasio (1986), who used the rotary pursuit task. AD patients and control subjects had to keep contact between a hand-held stylus and a target metal disk, the size of a coin, on a revolving turntable. In subsequent trials, control subjects increased the time that they were able to keep contact with the disk. AD patients had an initial level of performance that was 45% below that of control subjects. However, they showed normal improvement and retention after a delay of 30 minutes, and, after repeated training performed only 10% below control subjects. Eslinger and Damasio’s results have been replicated in a number of studies (Bondi & Kaszniak, 1991; Butters, Heindel, & Salmon, 1990; Corkin et al., 1986; Deweer et al., 1994; Heindel, Salmon, Shults, Walicke, & Butters, 1989), and there is evidence that AD patients can retain almost normally their rotary pursuit skill over a 4-week period (Deweer et al., 1994). AD patients show normal performance also in learning other motor skills. In a study by Gabrieli (1986), AD patients and control subjects were asked to trace a five-pointed star with a stylus without seeing their hand, the stylus, or the star except as reflected in a mirror. AD patients and control subjects made successively fewer errors and decreased the time needed to trace the star. Although not all the AD patients were able to perform the task, those who did showed long-term retention of the skill and were able to transfer normally their mirror-tracing skill from one pattern to another. Knopman and Nissen (1987) tested 28 AD patients on a visual serial reaction time task. They were given five blocks of 100 trials each. Unknown to the subjects, the trials in the first four blocks were arranged in a repeating 10-trial sequence. The trials in the last block appeared randomly in four different visual locations. Control subjects improved the speed of their reaction times across the four blocks of repeating trials. The improvement was attributed to the learning of the sequence, since in the fifth block reaction times slowed considerably. Although AD patients were slower than control subjects at this task, they improved their speed of response across the repeating-sequence blocks and showed the typical slowing when the block of random trials was administered. The examination of individual data, however, revealed that 9 of the 28 AD patients failed to show evidence of learning the sequence in that they had response times in the fifth random block that were as fast as or faster than shown in the last block of the repeating sequence trial. The 19 “learners” and the 9 “nonlearners” did not differ in terms of age, sex, severity of dementia, or scores on standard test of memory and language. They did differ, however, on two tests: the WAIS Block design and the Porteus Mazes. The poor performance of the “nonlearners” on these two visuospatial tasks suggests that the absence of the sequence-learning effect in these patients was

442 Dalla Barba, Boller, Rieu due to their poor visuospatial abilities, and not merely to a procedural learning deficit. Deweer et al. (1994) examined AD patients on a mirror-reading task adapted from Cohen and Squire (1980). Each of 30 AD patients together with 19 control subjects were presented with 50 cards, each presenting three words printed backward three times in 3 consecutive days. Five word triads were unique to each block and five were common to all blocks across the 3 days. The task proposed to the subjects was to read as quickly as possible the triads of words. The reading time was measured and recorded. They found that AD patients and control subjects showed the same pattern of procedural learning, in that the time to read the repeated triads significantly decreased across experimental sessions, whereas this was not the case for unique triads. Heindel, Salmon, and Butters (1990) administered a weightbiasing task to AD patients and to patients with Huntington’s disease (HD). They used two sets of 10 cylindrically shaped weights ranging from 35 to 485 g, in 50-g increments. During the biasing trials, the subjects were instructed to lift a series of weights and to judge whether each successive weight was heavier or lighter than the one that had just preceded it. The subjects were given 40 trials of either the five lightest weights (the light bias condition) or the five heaviest weights (the heavy bias condition). Subjects were then administered 10 test trials of weight judgment. They were told to lift and then judge each weight according to a 9-point scale (1 = extremely light; 9 = extremely heavy). The performance of AD, HD patients, and control subjects did not differ in the weight-biasing condition. All groups exceeded 90% accuracy in their judgment as to whether a given weight was lighter or heavier than the immediately preceding one. However, on the 10 test trials, AD patients and control subjects showed biasing effect: they judged weights heavier after a light bias condition than after a heavy bias condition, whereas HD patients did not show this biasing effect. Parkinson’s disease (PD) The prevalence of dementia and cognitive impairment in PD is 2–93% (Growdon & Corkin, 1986). This striking range of findings across different studies is due to many factors, including, among others, measures of cognition and operational definitions of dementia, and the heterogeneity of the disease itself (see Gabrieli, 1993, for a discussion). However, there is evidence that some, but certainly not all, PD patients have clinical dementia. The presence or the absence of dementia syndrome in PD patients obviously conditions their performance on memory tasks and on the pattern of impairment of different memory systems. As far as skill learning is concerned, there is evidence that nondemented PD patients perform normally on rotary pursuit learning despite their extrapyramidal motor disease, whereas demented PD patients fail to show normal learning on this task (Heindel et al., 1989). In this study, PD patients’

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impairment on rotary pursuit learning cannot be ascribed to their motor impairment or to the severity of dementia, because demented PD patients were not more motorically impaired than nondemented PD patients and were less demented than AD patients who showed normal learning on the task. Bondi and Kaszniak (1991) examined the performance of 16 PD patients on rotor pursuit learning and on a mirror-reading task and found that their performance was comparable to that of 16 control subjects. Huntington’s disease (HD) HD is a genetic, progressive, degenerative disorder in which the neuropathological changes are largely limited to the striatum, in particular the caudate nucleus. HD patients are impaired on some procedural memory tasks and this has been taken as evidence that the striatum plays a role in procedural learning (Heindel, Butters, & Salmon, 1988). Knopman and Nissen (1991) studied 13 HD patients and 12 normal control subjects on a serial reaction time (SRT) task. The SRT task was a four-choice reaction time task in which the stimuli followed a sequence (10 items in length) which repeated itself 10 times during each of the first four blocks of trials. During the fifth trial, the stimuli were random. Learning was manifested by a reduction of response latency over the first four blocks and an increase of response latency in the fifth block. Compared to controls, HD patients were significantly impaired on this task. In addition, the performance on this task did not correlate with other cognitive or motor performance. Similar results were obtained by Sprengelmeyer, Canavan, Lange, and Homberg (1995). Heindel et al. (1988) examined the performance of HD patients, AD patients, amnesics, and normal controls on a rotor pursuit task. Differences between groups in the baseline performance were minimized by adjusting the rotation speed of the disk. The results showed that while AD patients, amnesic patients, and normal controls improved their time on target over six test blocks, HD patients were severely impaired in the acquisition of this motor skill. These results were replicated in a further study (Heindel et al., 1989). Martone, Butters, Payne, Becker, and Sax (1984) examined the performance of HD patients, amnesic patients, and normal controls on a mirror-reading task and found that while over test blocks amnesic patients acquired the mirror-reading skill at a normal rate, HD patients were impaired in the acquisition of this skill. Rebok et al. (1995) tested the influence of neurological and cognitive impairment of HD patients on automobile driving. In a group of 73 HD outpatients, 53 continued to drive after illness onset. Twenty-nine HD patients who were still driving and 16 healthy control subjects underwent a clinical examination, a cognitive examination, and a driving-simulator task. HD patients performed significantly worse than control subjects on the driving-simulator task and were more likely to have been involved in a collision in the preceding 2 years.

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Perceptual representation system (PRS) The PRS is involved in identifying words and objects, it operates at a presemantic level, and it is typically involved in nonconscious or implicit expressions of memory, such as priming. It emerges early in the development, and access to it lacks the flexibility characteristics of other memory systems. Evidence for postulating the existence of the PRS as a distinct memory system comes from two independent and converging lines of research. On the one hand, it has been shown that perceptual priming can be dissociated from explicit remembering both in normal subjects and amnesic patients (Tulving & Schacter, 1990). On the other hand, neuropsychological research indicates that patients with severely impaired semantic knowledge may show relative preservation of access to lexical/structural knowledge of material for which they cannot access the meaning (Schacter, 1990). The subsystems presented in Table 22.1 include the visual-word-form, auditory-word-form, and structural-description subsystems. Although they probably do not represent a complete list of PRS subsystems, various kinds of evidence suggest that they are distinct subsystems. They all share some common characteristics: (1) they operate at a presemantic level, that is, at a level of processing that does not require access to the meaning of words and objects; (2) they are involved in nonconscious expression of memory; and (3) they are all likely to depend on cortical mechanisms (Schacter, 1994). The three subsystems, however, differ in the kind of information they process. Visual and auditory form of words Priming is a form of human memory that refers to unconscious facilitation of perceptual identification of words and objects following prior exposure to a target item or a related stimulus. Most studies examining perceptual priming in AD have used word-stem completion tasks. In a word-stem completion task, subjects are required to complete a word stem (for example, sta) with the first word that comes to mind (Warrington & Weiskrantz, 1970). The stems are generally selected to have several possible completions, and of interest is whether prior presentation of an appropriate completion of a stem (for example, stamp) increases the probability of its generation. This is assessed by comparing the probability of completing stems with specific completions (targets) when these have (primed condition) or have not (unprimed condition) been presented in the experimental setting prior to the completion task. Normal subjects are known to provide the words seen in the study phase at a rate well above chance, and so are amnesic patients (Graf, Squire, & Mandler, 1984; Warrington & Weiskrantz, 1970).

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Aging Several studies have contrasted the performance of young and older adults on episodic memory tasks and perceptual priming. Light and Singh (1987) compared the performance of young and older adults on free recall, cued recall, and perceptual priming. They found that older subjects performed significantly less well than young subjects on most of the recall and recognition measures, but were unimpaired in the priming task. In another study, Light, Singh, and Capps (1986) compared the performance of young and older adults on an episodic memory recognition task and a word fragment completion task. Older subjects performed significantly worse than the young subjects on the episodic memory task but showed a normal priming effect on the fragment completion task. Schacter (1994) examined the performance of young and older subjects on an auditory stem completion and filter identification task. They found that young subjects showed more priming when the speaker’s voice was the same at study and test than when it differed, whereas elderly subjects failed to exhibit this voice-specific priming effect. They did show, however, a robust nonspecific priming effect. AD In contrast to what is true for normal subjects and amnesic patients, data concerning perceptual priming in AD are quite controversial. Some studies (Gabrieli, 1986; Heindel et al., 1989; Salmon, Shimamura, Butters, & Smith, 1988; Shimamura, Salmon, Squire, & Butters, 1987) found significantly reduced stem-completion priming in AD, and this was true also when priming in AD was compared to priming in amnesic patients, whose recall and recognition scores were no better than those of AD patients, but whose stemcompletion priming was equivalent to that of normal subjects (Gabrieli, 1986; Shimamura et al., 1987). Other studies, however, have shown that perceptual priming is relatively preserved in AD. Indeed, there are now nearly as many studies showing intact as there are showing impaired perceptual priming in AD (Fleischman & Gabrieli, 1998). The understanding of why perceptual priming deficit occurs or does not occur in AD is still scant, and its development is probably contingent on the consideration of multiple interactions between subject-related and task-related factors (Fleischman & Gabrieli, 1998). It is well known from lesion studies in amnesic patients who show dramatic impairment of episodic memory but normal perceptual priming that a widespread network of brain regions, including medial-temporal, diencephalic, and frontal structures, is involved in episodic remembering. By inference, these regions should play a relatively limited role in perceptual priming. Indeed, regions in the posterior occipital cortex seem to be involved in perceptual priming (Fleischman, Gabrieli, Reminfer, Rinaldi, & Wilson, 1995). This inference is consistent with recent data from functional neuroimaging

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studies. Bäckman, Almkvist, Nyberg, and Andersson (2000) studied perceptual priming in normal old adults and mildly demented AD patients with positron emission tomography (PET). Compared with normal old adults, AD patients showed reduced priming on a word-stem completion task. The normal old adults showed decreased activity in the right occipital cortex (area 19), whereas AD patients showed increased activity in this region during priming. According to the authors, the different patterns of increased/ decreased activation in occipital regions in AD patients and normal old adults indicate that on a word-stem completion task AD patients fail to activate neural structures involved in explicit remembering and can rely only on the perceptual characteristics of the stimuli activating the primary visual cortex. Parkinson’s disease (PD) The level of performance of PD patients on perceptual priming tasks is contingent on the presence or absence of dementia. Heindel et al. (1989) examined the performance of nondemented and demented PD patients on a word-stem completion priming task and found that nondemented patients exhibited normal levels of priming, but the demented PD patients had significantly reduced levels of priming. Koivisto, Portin, and Rinne (1996) compared the performance of PD and AD patients on measures of explicit recognition memory and perceptual priming. Both patient groups were equally impaired on explicit memory and unimpaired on perceptual priming tests. Ivory, Knight, Longmore, and Caradoc-Davies (1999) studied the performance of 20 nondemented PD patients and 20 healthy controls on a series of explicit and implicit memory tasks. The PD patients’ performance on perceptual priming was found to be normal. Huntington’s disease (HD) Randolph (1991) administered a priming task involving a word-stem completion paradigm to AD patients, HD patients, and normal control subjects. They found that HD patients showed a normal priming effect that was significantly higher than that shown by AD patients. Structural description Evidence for the existence of a structural description subsystem comes from studies on young, normal subjects. Schacter, Cooper, and Delaney (1990) and Schacter (1994) developed a paradigm for examining priming of structural descriptions. They used two-dimensional line drawings that depict unfamiliar three-dimensional objects. Although all the objects are novel, half of them are structurally possible (they could exist in three-dimensional form), whereas the other half are structurally impossible (they contain surface and edge

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violations that would prohibit them from existing in three dimensions). In their experiment, subjects were first given a list of possible and impossible objects and then were given an object-decision test to assess priming. For the object-decision test, previously studied and unstudied objects were presented one at a time for 50–100 ms, and subjects decided whether they were possible or impossible. Schacter et al. (1990) observed a priming effect for structurally possible, but not for structurally impossible, objects. According to the authors, failure to observe priming for impossible objects may indicate that it is difficult to form an internal representation of the global structure of an impossible object. Consistent with this observation, priming on the object-decision task was observed in amnesic patients (Schacter, Cooper, & Treadwell, 1993). At present, however, there are no studies concerning the structural description subsystem in aging and age-related neurological diseases.

Primary memory Primary memory, or short-term memory (STM), is a system that allows a limited amount of information of various kinds to be retained over short periods of time. It is typically involved in carrying out various kinds of cognitive tasks, and it involves complex and still not fully understood relations with long-term memory (LTM), that is, the other four memory systems. Working memory (WM) represents a more elaborated version of primary or STM (Baddeley & Hitch, 1974). Baddeley (1994) defined WM “as the system for the temporary maintenance and manipulation of information, necessary for the performance of such complex cognitive activities as comprehension, learning and reasoning”. According to Baddeley and Hitch’s model (1974), WM is composed of three subsystems: the phonological loop, the visuospatial sketchpad, and the central executive (CE). The phonological loop enables phonological material in a phonological store to be maintained by a recycling process. Several phenomena observed in normal subjects and in braindamaged subjects are captured by postulating the existence of such WM subsystems (see Baddeley, 1994, for details). The visuospatial sketchpad is involved in storing a limited quantity of visuospatial information for a limited time. However, experimental evidence of the existence of this WM subsystem is rather scant. In Baddeley’s model, both subsystems, the phonological loop and the visuospatial sketchpad, operate under the control of the third WM subsystem, the CE. Because of its control role on the two other subsystems, the CE is assumed to be the most important within WM. However, its real existence and its neural bases are rather controversial. Baddeley (1986) proposed to use Norman and Shallice’s (1980, 1986) model of attentional control as a working hypothesis for the CE. This model assumes that action can be controlled at either of two levels: by the operation of a series of existing schemata or via the supervisory attentional system, which takes control when novel tasks are involved or when existing habits have to be overridden. Within the WM hypothesis, Norman and Shallice’s model may help to

448 Dalla Barba, Boller, Rieu understand the function of the CE. However, both the CE and Norman and Shallice’s supervisory attentional system are difficult to be accepted for at least two reasons: (1) they lack specificity, that is, the spectrum of their activities is too wide to consider them as specific cognitive systems; (2) their neural substrate is controversial. They are assumed to be based on the frontal lobe and related structures, but, in fact, patients showing symptoms that should be ascribed to a deficit of these systems may show the following: (1) normal performance on tasks considered sensitive to an executive/attentional disorder; (2) intact frontal and related structures; (3) executive/attentional disorders associated with lesions in posterior brain regions. Future research will tell whether the CE/supervisory attentional framework should be definitely abandoned or completely reframed. It must be pointed out that the precise boundaries of the WM are not easy to define. For instance, it has been stated that the Token Test (De Renzi & Vignolo, 1962), usually considered as a “typical” test of auditory comprehension, actually deals with the WM (Caplan & Waters, 1999; Lesser, 1976). Aging The recency effect in free recall of word lists has been taken to reflect STM capacity. Parkinson, Lindholm, and Inman (1982) found a loss of the recency effect in older adults. However, this age-related decrement was as great in recency as in earlier portion of the serial position curve, and they concluded that both STM and LTM are affected by aging. Craik and Rabinovitz (1984) proposed that STM is unaffected by aging. The discrepancy between Parkinson et al.’s results and Craik and Rabinovitz’s results may be traced back to the fact that while the former authors used a task in which both STM and LTM were involved, the latter used relatively pure measures of STM. If these kinds of measures are used, age-related differences are slight or nonexistent. As far as span is concerned, there is evidence of a small but reliable agerelated decrement in digit span (Johansson & Berg, 1989; Parkinson, 1982). Babcock and Salthouse (1991) showed that word span declines more with age than digit span, and this result is in line with results reported by other authors. Overall, it seems that memory span does show a small drop with age. There is some evidence, however, that span contains both STM and LTM components (Parkinson et al., 1982). If so, the age-related decrease in span performance may be attributable to the LTM component of span. As far as WM is concerned, there is almost general agreement that older people do less well on WM tasks, and that such age differences can be traced to a variety of age-related deficits in cognitive performance (Craik & Jennings, 1992). In a recent study, West (1999) examined the effects of taxing selective attention processes on the efficiency of WM processes in normal aging. In both experiments, the presence of task-irrelevant information impaired the efficiency of WM, and the effect was greater for older than younger adults.

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According to his findings, the author suggests that distraction disrupts both the ability to maintain a coherent stream of goal-directed thought and action in younger and older adults and the encoding and retention of relevant information in older adults. Baddeley, Cocchini, Della Sala, Logie, and Spinnler (1999) examined vigilance performance in elderly subjects who were tested over a 40-minute period in perceptual or memory-based tasks. They found a significant decrement only in the memory task. This result is in line with the results obtained by Craik, Govoni, Naveh-Benjamin, and Anderson, (1996) and Naveh-Benjamin, Craik, Guez, and Dori (1998) that showed that divided attention at encoding affects performance on the memory task, but not on the perceptual secondary task. Palladino and De Beni (1999) examined the performance of young, old, and old-old subjects on a WM task. They found a continuous decline in WM measures, and an early decline in STM across groups. As far as the neural substrates of WM are concerned and as far as PET studies can reveal, there is preliminary evidence (Reuter-Lorenz et al., 2000) that in young adults left frontal structures activate in verbal WM tasks, and that right frontal structures activate in spatial WM tasks. In contrast, older subjects show a global pattern of anterior bilateral activation for both verbal and spatial WM. AD A number of studies have assessed primary memory in AD patients. One approach has been to give subjects lists of words and examine their free-recall accuracy as a function of the serial position of the stimulus words. Normal adults, both young and old, typically show a U-shaped function in which recall is better for the first items (primacy effect) and for the last items (recency effect) of the list, than for those falling in the middle of the list (Buschke & Hinrichs, 1968; Buschke & Kintsch, 1970). The recency effect is assumed to reflect STM, whereas the primacy effect is supposed to reflect LTM. Some studies (Wilson, Bacon, Fox, & Kaszniak, 1983) examined the serial position effect in normal individuals and AD patients. The results showed a mild decrease in the recency portion of the curve and a major decrease in the primacy portion, suggesting that STM is relatively spared in AD compared to LTM. Spinnler, Della Sala, Bandera, and Baddeley (1988) corrected subjects’ primacy and recency effects on the basis of subjects’ performance on items in the middle portion of the serial position function and found no difference in the size of the recency effect but a large difference between AD patients and normal controls in the primacy effect, suggesting a relative preservation of STM in AD. Another commonly used measure of STM in AD is the memory span. Studies that have assessed span in AD patients have consistently shown a decrease in memory span. In AD patients, memory span is generally reduced for words (Belleville, Peretz, & Malenfant, 1996; Hulme, Lee, & Brown, 1993;

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Morris, 1984), letters (Belleville et al., 1996; Dannenbaum, Parkinson, & Inman, 1988; Spinnler et al., 1988), digits (Belleville et al., 1996; Cherry, Buckwalter, & Henderson, 1996; Kopelman, 1985; Morris, 1987; Orsini, Trojano, Chiacchio, & Grossi, 1988), and spatial location (Grossi, Becker, Smith, & Trojano, 1993; Orsini et al., 1988; Spinnler et al., 1988). However, although reduced in comparison to normal old subjects, the memory span in early and moderate AD patients is relatively preserved compared to their performance on tasks tapping explicit LTM. As far as WM is concerned, it is generally agreed that AD patients show a deficit of executive functions, that is, the functions underpinned by one of the components of the WM system, namely the CE (Baddeley, Bressi, Della Sala, Logie, & Spinnler, 1991). At least in the very early stage of the disease, there is a clear dissociation between the impairment of the CE and the relative preservation of the “slave” subsystems of WM, namely the articulatory loop and the visuospatial sketchpad (Spinnler, 1999). Patients at this stage of the disease typically show great difficulty in performing two different tasks simultaneously and in manipulating information maintained in working memory, features that, in Baddeley and Hitch’s model (1974), are compatible with a deficit at the level of the CE. Although the majority of studies agree with the interpretation of a CE deficit in AD WM, some studies emphasize the role of phonological loop impairment in AD patients, even in the early stage of their disease (Belleville et al., 1996; Hulme et al., 1993; Miller, 1972). In a recent study, Collette, Van der Linden, Bechet, and Salmon (1999) examined the functioning of the phonological loop and the CE in AD patients and normal old adults. AD patients showed abnormal functioning of the phonological loop and decreased performance on tasks assessing the CE. However, interestingly enough, when AD patients were separated into two groups on the basis of their span level, both groups showed deficits of the CE, but only patients with a lower span level presented a dysfunction of the phonological loop. Consistent with their findings, the authors interpreted this dissociation in terms of the severity of the disease: patients with a high span level were less severely demented and displayed only deficits in higher level cognitive functions, whereas patients with a low span level had impairments encompassing a series of more basic processes. Parkinson’s disease (PD) Several studies have measured memory span in PD patients, but the results vary significantly from one study to another. On the WAIS digit span (forward and backward combined), PD patients usually perform as well as normal control subjects (Horn, 1974; Lees & Smith, 1983). Another study (Asso, 1969) showed better WAIS digit span scores in PD patients than in age- and gender-matched controls. Even when forward and backward digit spans are reported separately, no difference emerges between PD patients and normal controls (Blonder, Gur, Gur, Sayjin, & Hurtig, 1989; Canavan, Passingham, Marsden, Quinn, & Polkey, 1989; Stern, Mayeux, & Cote, 1984). One study

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found that PD patients, compared to control subjects, were impaired in forward, but not in backward, digit span (Marsh, Markham, & Ansel, 1971), and other studies found digit span significantly reduced in PD patients compared to normal controls (Della Sala, Lorenzo, Giordano, & Spinnler, 1986; Fournet, Moreaud, Roulin, Naegele, & Pellat, 2000; Marsh et al., 1971; Pirozzolo, Hansch, Mortimer, Webster, & Kuskowski, 1982). However, even when statistical significance is not reached, in all studies in which scores were reported, small effects have been observed, suggesting that it is likely that there is a small but real difference in memory span between PD subjects and normal controls (Howard, Binks, Moore, & Playfer, 2000). If primary memory as measured by the memory span is almost normal or only slightly impaired in PD patients, WM is generally found to be clearly impaired in PD (Brown & Marsden, 1988, 1991; Dalrymple-Alford, Kalders, Jones, & Watson, 1994; Fournet et al., 2000; Robertson, Hazlewood, & Rawson, 1996). Dalrymple-Alford et al. (1994), for example, tested PD patients on a dual-task paradigm developed by Baddeley, Bressi, Della Sala, Logie, and Spinnler (1991) and Baddeley, Logie, Bressi, Della Sala, and Spinnler (1986). In this study, subjects performed a random pursuit while recalling forward digit-span sequences. PD patients scored as the control subjects when the two tasks were performed separately, but showed a poorer performance than control subjects when the two tasks were combined. The results of this and other studies show that PD patients have difficulty in performing two tasks simultaneously, and this may be interpreted as reflecting a CE deficit. Huntington’s disease (HD) Wilson, Como, Garron, Klawans, Barr, and Klawans (1987) have studied word-list recall in HD patients and found that recall attributable to STM is normal. Lange, Sahakian, Quinn, Marsden, and Robbins (1995) have studied the performance of HD patients relatively late in the course of their disease on tasks of executive and mnemonic functions. HD patients were significantly impaired on tasks of executive functions and on a test of spatial span. Lawrence et al. (1996) studied a group of patients with early HD on tests of spatial span, spatial working memory, and spatial planning. HD patients were found to be impaired on both visuospatial and executive functions. Similar results were obtained in a more recent study (Lawrence, Watkins, Sahakian, Hodges, & Robbins, 2000), confirming the suggestion that spatial WM is impaired in HD and that the basal ganglia play a relevant role in spatial WM.

Semantic memory Semantic memory refers to the knowledge of words and the meanings of concepts and facts, knowledge of symbols and rules to manipulate symbols. It ultimately represents the corpus of knowledge and information shared by

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the members of the same society. In other words, semantic memory enables the acquisition and retention of factual information about the world in the broadest sense. The knowledge about the world, whether concrete or abstract, general or specific, that people possess or acquire, and their beliefs and expectations, are strongly dependent upon semantic memory. It must be emphasized, however, that semantic memory is a very general concept. Although there are good theoretical and empirical arguments for unifying under the same general concept a number of quite different modes of acquisition and expression of knowledge, it is worth bearing in mind that differences within the semantic system are as numerous as similarities. While meaning or symbolic knowledge is the hallmark shared by every aspect of semantic memory, its expression can vary according to modality, as in implicit versus explicit material, verbal versus nonverbal level of processing, automatic versus voluntary type of knowledge, word meaning versus general knowledge, and categories, as in living versus nonliving items. Even if we look at some particular aspects of SM, such as its categorical organization, we find that some crucial questions are still open. Neuropsychological evidence has consistently shown that semantic memory is organized in several different categories of knowledge. Although the fractionation of knowledge in different categories is a well established and reproducible phenomenon, its nature remains still unclear and ambiguous. In particular, it is unclear whether the dissociation observed between categories of items, as in living versus nonliving items, is genuine or whether it should be traced back to other, more basic dissociation, such as the knowledge of perceptual versus functional attributes of objects. A second important issue in the organization of semantic memory concerns its relationship with episodic memory. Episodic memory enables people to remember episodes witnessed in their own personal past. In other words, episodic memory underpins the conscious recollection of one’s own past. Episodic memory is assumed to be the most recently evolved memory system, both in phylogeny and ontogeny, and has grown out of semantic memory (Tulving, 1983, 1984b). This assumption has two important implications, the first being that episodic memory is, in fact, a subsystem of semantic memory, and the second that semantic and episodic memory at least partially overlap in terms of both the type of information and their neural correlates. As we will see later, both these implications are controversial, and many students of memory systems think that episodic and semantic memory are two parallel and independent memory systems. It must be noted, finally, that some researchers doubt the need to distinguish between semantic and episodic memory systems. The fact that both these systems are similarly impaired, as in many cases of amnesia, partially supports this view. In this chapter, however, we will maintain the distinction between episodic and semantic memory because we think that the reasons for making such a distinction are stronger than the reasons against a distinction.

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Aging Although semantic memory abilities are affected much less than episodic memory abilities in normal aging, there is evidence of possible age differences in representation of word meanings. Overall, compared to young adults, elderly subjects show difficulty in word finding, responses to word association tasks, naming, and judgment of similarity or relatedness of concepts (Light, 1992). Word-finding difficulty in normal aging can manifest itself in several ways. Elderly subjects may use pronouns without antecedents (Obler, 1980; Pratt, Boyes, Robins, & Manchester, 1989) and show in spontaneous speech increased frequency of pauses, which may signal word-finding problems. Declines in verbal fluency are also reported in studies of normal aging (Obler & Albert, 1985), although they are not always found. Decreased verbal fluency should not, however, be taken as evidence of loss of verbal meaning in old age. Other factors, such as failure to access the phonological form of words or a decline in strategic search abilities, may play a confounding role in verbal fluency decline in elderly subjects. However, older adults do have more word-finding difficulty than young adults. For example, they have more tipof-the-tongue experiences in which words are temporarily unretrievable, but eventually do become available (Burke, McKay, Worthley, & Wade, 1991). Older adults also show more difficulty than young adults in picture-naming tasks, though usually this difficulty does not become evident until the eighth decade of life (Albert, Heller, & Milberg, 1988). In naming tasks, old adults’ typical errors are semantically related words and circumlocutions (such as “cutting the wood” for “sawing”). These kinds of errors, however, are more in keeping with lexical retrieval failures than with semantic deficits, since phonemic cues are equally helpful as hints to young and older adults and semantic cues are not very helpful to either age group (Nicholas, Obler, Albert, & Goodglass, 1985). In conclusion, although older adults may show a variety of difficulties compared to young adults in word-finding, naming, and other tasks such as word associations or judgment of similarity, the most likely explanation for these deficits is that lexical access is impaired in older adults. However, there is little or no evidence for age-related changes in semantic memory. AD In 1975, Warrington published data from three patients whose semantic memory deficits were examined in the early stage of their progressive neurological pathology. The author found that these patients showed selective difficulties in accessing the meaning of words and objects in the context of preserved visuoperceptual functions, linguistic processes, and general intelligence. These results were taken as the first reported evidence that semantic memory can be selectively impaired when other cognitive systems are intact.

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One of the most commonly reported dissociations in AD is the selective impairment of knowledge of objects in the natural physical world and manmade artifacts. By far, the most common pattern of dissociation is that encompassing categories labeled as “living things” and those labeled as “nonliving things”. The living category is more vulnerable to loss of comprehension, recognition, or naming and is found to be consistently affected in AD patients. Montanes and coworkers (Montanes, Goldblum, & Boller, 1995, 1996) have shown that AD patients are impaired both in naming and classification of living items compared to nonliving items even in the early stage of their disease. A selective deficit for knowledge of living items in AD patients has been reported in a number of other studies (Chertkow, Bub, & Caplan, 1992; Silveri, Daniele, Giustolisi, & Gainotti, 1991), although at least one study failed to replicate these findings (Tippette, Grossman, & Farah, 1996). In a recent study, Fung, Chertkow, and Templeman (2000) examined the performance of AD patients on a semantic association judgment task in which they had to decide which of the two presented words mostly resembled the target item (e.g. lamb: goat, sheep). The experimental material was drawn from six different categories. Compared to control subjects, AD patients made significantly more errors in abstract and living items, but not in verbs and nonliving items. This pattern of results has been documented in patients with temporal lobe damage, suggesting that the early damage to temporal structures in AD may be crucial for the category-specific impairment that these patients show. The fact that AD patients are better in naming verbs than nouns, as demonstrated by some studies (Cappa et al., 1998; Fung et al., 2000), may be due to the sparing of frontal structures in the early stage of the disease. However, the nature of semantic category-specific deficits in AD still remains unclear. Moreover, with the progression of the disease, all categories of knowledge are severely impaired, no matter which task is employed. For example, in some cases there is a relative sparing of superordinate knowledge; that is, patients may no longer know that an apple is an apple, but they may still know that it is a fruit. For example, Chertkow and Bub (1990) found that AD patients performed at the same level as control subjects in answering questions concerning superordinate items, but they made 90% of errors for questions concerning the subordinate. In general, with the progression of the disease, there is a gradual deterioration of the organization and content of semantic memory. Semantic knowledge of concepts and their attributes is actually lost during the course of the disease as the result of the degradation of cortical association areas. This loss of semantic knowledge results in concepts becoming less well defined, and their distinguishing attributes are eliminated. In a recent longitudinal study on AD patients, Salmon, Heindel, and Lange (1999) assessed the ability to generate words of phonemic (that is, words beginning with a given letter) and semantic categories. AD patients performed worse than control subjects on both tasks at each of four annual evaluations and they exhibited greater impairment than control subjects on the semantic task than on the phonemic

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task. The performance of AD patients declined over time on both tasks, but the rate of decline was faster on the semantic category than on the phonemic category task. These results are actually consistent with the notion that AD patients suffer a gradual deterioration of the organization and content of semantic memory as the disease progresses (Salmon et al., 1999). PD The status of semantic memory in PD is quite controversial. The inconsistency of results in the literature reflects the inconsistency of methods used to assess semantic memory and, above all, the great variance in semantic memory performance of PD patients as a function of their mental status, that is, the presence or absence of cognitive decline and dementia. It has been proposed that many of the cognitive deficits observed in PD reflect the difficulty with the initiation and execution of internally guided information-processing strategies that are related to cortico-striatal-thalamo-cortical loop pathophysiology (Taylor & Saint-Cyr, 1995; Tröster & Fields, 1995). Accordingly, it would be expected that PD patients are impaired in verbal fluency tasks that require the active execution of internally guided retrieval of information. To date, however, data on the verbal fluency in PD patients have been inconsistent. The methodology and the differences in the mental status of PD patients in different studies may account for this inconsistency of results. For example, Gurd and Ward (1989) identified both phonological and semantic fluency deficits in a sample of PD patients, but no information regarding the overall level of cognitive functioning of the subjects was provided. However, even when PD patients without cognitive decline are considered, findings are still notably inconsistent. Some studies have found no semantic or phonological fluency deficits in PD patients, whereas others have found deficits on both tasks (Bayles, Trosset, Tomoeda, Montgomery, & Wilson, 1993), and still others have found deficits in semantic, but not in phonological, fluency (Auricombe, Grossman, Carvell, Stern, & Hurtig, 1993). In a recent study, Piatt, Fields, Paolo, Koller, and Troster (1999) compared phonological, semantic, and action fluency in groups of PD patients with and without dementia. Results showed that PD demented patients had significantly poorer performance than nondemented PD patients on all fluency tasks, and particularly on the action fluency task. PD nondemented patients performed at the same level as control subjects on all tasks. Controversial data on PD patients show that semantic fluency is, at least in some cases, impaired. However, it is difficult to conclude that a semantic deficit is present in these patients, since their difficulties in semantic fluency tasks could be simply traced back to a lexical access deficit. Whether PD patients are actually affected by a real semantic memory deficit remains unclear. In a recent study, however, Portin, Laatu, Revonsuo, and Rinne (2000) compared the performance of nondemented PD patients and PD patients with mild cognitive deterioration on tasks of verbal descriptions of abstract and concrete

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concepts, concept attributes, and conceptual hierarchies. Nondemented PD patients were as good as control subjects on all tasks, whereas PD patients with mild cognitive impairment showed semantic memory disruption. HD As in the case of PD, the status of semantic memory in HD is contingent on the presence or absence of cognitive decline and dementia. If cortical association areas are involved, HD patients usually show a general cognitive decline, including semantic memory. However, at the early stage of the disease, when motor impairment is the most prominent clinical symptom, semantic memory, as well as other cognitive functions, is preserved or only mildly impaired. In a recent study, Rohrer, Salmon, Wixted, and Paulsen, 1999 examined the response latencies on a semantic fluency task in HD and AD patients. They found that HD patients produced more responses than AD patients, but response latencies were longer, suggesting a retrieval deficit in HD patients. However, as pointed out earlier, verbal fluency tasks are more sensitive to lexical access than to semantic knowledge. Accordingly, it is difficult to conclude that there is a semantic deficit in HD, at least at the early stage of the disease. As the disease progresses, motor impairment and other psychiatric and cognitive deficits act as confounding factors, hindering understanding of the specific role of a semantic memory impairment in these patients.

Episodic memory As mentioned earlier in this chapter, episodic memory is the most recently evolved memory system, both in ontogeny and phylogeny. Episodic memory enables conscious recollection of personal happenings and events from one’s own past (Tulving, 1972, 1983). In laboratory conditions, episodic memory is measured by recall and recognition tasks, such as recall and recognition of word lists in which each word is considered as a “mini-personal past episode”. As we will see later, episodic memory is associated with a particular subjective experience or type of consciousness (Dalla Barba, 2001; Tulving, 1985; Wheeler, Stuss, & Tulving, 1997). In this view, episodic memory refers to a subordinate structure of temporality, the personal past, and is closely linked to the other structures of temporality, namely personal past and personal future. According to its ontological and phylogenetic status, episodic memory is the most vulnerable memory system and is therefore affected in normal aging and early in the course of age-related neurological diseases. Aging Many studies have documented a reduction in episodic memory abilities in normal aging (see Burke & MacKay, 1997, for a review). Mitchell, Brown, and Murphy (1990) compared the performance of young and older adults on

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a recognition memory task of pictures that subjects had previously named and found that recognition was significantly lower in older adults. Bäckman (1991) examined the influence of prior knowledge on recognition memory in young adults, younger old adults (76 years old), and old-old adults (85 years old). In experiment 1, they examined recognition memory of dated and contemporary famous people. In experiment 2, they presented four types of faces for later recognition: dated familiar, contemporary familiar, old unfamiliar, and young unfamiliar. The results of both experiments showed that young adults performed better with contemporary than with dated famous persons, whereas the reverse was true for all groups of older adults. In addition, experiment 2 showed that young adults showed better recognition of young than old unfamiliar faces, young-old adults showed better recognition of old than young unfamiliar faces, but old-old adults showed no effect of age of face. These results are interpreted as suggesting that the ability to apply rich semantic information to improve episodic memory is preserved in very old age, although the aging process may be associated with deficits in the ability to utilize prior knowledge to support episodic memory when the underlying representation lacks semantic and contextual features. Spencer and Raz (1995) reviewed the evidence of age differences in episodic memory for content of a message and the context associated with it. The results of the meta-analysis of 46 studies showed that age differences in context memory are reliably greater than those in memory for content. The authors suggest that impaired memory for context in the elderly can be traced to reduced attentional capacity, which is more important to encode context than content of episodic memory. However, the detrimental effect on episodic memory of reduced attentional resources in old adults is quite controversial. Nyberg, Nilsson, Olofsson, and Backman (1997) examined the effects of dual-task requirements on age differences in free recall performance: 1000 adults aged 35–80 years performed a word-recall task alone and concurrently with a card-sorting task (at encoding, retrieval, or both). Age differences in memory performance were substantial under single-task conditions, but not under dual-task conditions. These results do not support the hypothesis that reduced attentional capacity in old age underlies age differences in episodic memory. Mark and Rugg (1998) examined the performance of young and old adults on a recognition memory task. In the study, subjects listened to words spoken by either a male or a female voice. In the test, subjects made initial old/new judgments to visually presented words. For words judged old, they indicated either in which voice they had heard the word at study (source task), or whether they “remembered” or “knew” they had heard the word at study (the “remember/know” task will be discussed later). The accuracy of recognition did not differ between groups. However, young subjects were significantly more accurate in the source judgment than old subjects. These results, inconsistently with other results in the literature, suggest that episodic memory is unaffected by aging, whereas source memory is affected by aging. Memory for the source of information, however, is part of episodic memory,

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and it is therefore imprudent to conclude for normal episodic memory in aging. AD An episodic memory deficit is the hallmark of AD, and AD patients must have such a deficit to meet the DSM-V (American Psychiatric Association, 1994) diagnostic criteria for dementia. Many studies have documented the episodic memory impairment in AD patients. However, the episodic memory deficit in AD patients may take different forms, and its origin may be traced to different cognitive mechanisms. One of the most striking aspects of episodic memory impairment in AD is the rapidity at which information is forgotten. Rapid forgetfulness is one of the factors on which screening and diagnostic tests of AD are based (Buschke et al., 1999; Buschke, Sliwinski, Kuslansky, & Lipton, 1997). However, rapid forgetfulness does not involve all the to-be-remembered items. It is well known, for example, that in free recall of word lists, AD patients show a normal, or close to normal recency effect; that is, they remember the last two or three items of the list better than the items in the middle of the list (e.g. Buschke & Hinrichs, 1968), but they do not show a normal primacy effect; that is, contrasted with normal controls, they do not remember better the first two or three items of the list. In a recent study, Burkart, Heun, and Benkert (1998) examined serial position effects for immediate and delayed free recall in AD patients and normal controls. Subjects were asked for immediate and delayed free recall of 12 drawings of common objects. Primacy effects were obtained at all delays in normal controls. By contrast, primacy effects were significantly impaired in AD patients at all delays of recall. The level of availability of attentional resources also seems to play a role in episodic memory performance in the early stage of AD. Perry, Watson, and Hodges (2000) examined the relationship between attention and episodic memory in the earliest stage of AD. They tested 27 patients with minimal cognitive impairment or with mild AD on tests of attention and episodic memory. Examination of the relationship between attention and other cognitive domains showed impaired episodic memory in all patients. Although attention is impaired in AD, in this study 40% of patients showed deficits in episodic memory alone, confirming that amnesia may be the only cognitive deficit in the earliest stage of sporadic AD. There is some evidence that the episodic memory deficit in AD is attributable to a deficit of encoding and storage of information rather than to a retrieval deficit. Green, Baddeley, and Hodges (1996), for example, analyzed the episodic memory deficit in early AD. They tested 33 patients with AD on episodic memory recall and recognition. They found no evidence for differential sensitivity of recall over recognition. This result suggests that the episodic memory deficit is one of learning rather than of the retrieval of learned material. Episodic memory performance in AD depends on the integrity of semantic memory abilities. Dalla Barba and Goldblum (1996) demonstrated

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that the ability of patients to make a semantic association between two items was significantly and positively correlated with their performance on a yes/no recognition task for the same items, and that patients who were impaired on the semantic task scored significantly worse on the recognition task than patients who were unimpaired on the semantic task. In a more recent study, Goldblum et al. (1998) further investigated the relationship between semantic memory deficits and episodic recognition memory in AD patients as a function of their semantic and perceptual encoding abilities. The results confirmed the previous findings and showed that, although patients heavily relied on perceptual analysis, this type of encoding did not enhance their recognition memory. Overall, these findings support a hierarchical model of organization of human memory in which episodic memory depends on the integrity of semantic memory. Patients with AD not only fail to retrieve episodic information but also suffer from distortions of memory. These memory distortions can sometimes be very severe, as in the case of delusional syndromes (Forstl, Besthorn, Burns, Geiger-Kabisch, Levy, & Sattel, 1994). Although they are usually less pronounced, they can still limit or abolish patients’ ability to live independently. Patients may, for example, believe that they did a certain act (paying a bill) when they only thought about it, or pay the bill twice because they think they have not done so. However, although memory distortions in AD are definitely a relevant component of their clinical picture, the nature of this disorder remains unclear. Studies on memory distortions in AD patients have been mainly devoted to their tendency to produce unstudied items or “intrusions” on learning memory tests. Fuld, Katzman, Davies, and Terry (1982) showed that intrusions are common in AD and that they correlate with the number and quality of pathological changes observed at autopsy. They concluded that intrusions are characteristic of AD and that they can be considered a diagnostic tool. Dalla Barba, Parlato, Iavarone, and Boller (1995) and Dalla Barba and Wong (1995), however, found that intrusions are not specific to AD and that they are common also in amnesia and in primary depression. They found that when AD and amnesic patients were required to retrieve a list of semantically related words, the production of related intrusions was associated with the absence of a semantic memory deficit. Dalla Barba et al. (1995) also found that intrusions were not correlated to the performance on tests of executive functions. In contrast, intrusions were correlated with the level of anosognosia for the memory deficit. Another type of memory distortion found in AD patients is confabulation, which must be distinguished from misidentification (Mattioli et al., 1999). Confabulation refers to a particular memory disturbance, observed in some brain-damaged patients, which consists of both actions and verbal statements that are unintentionally incongruous to history, background, and present situation (Dalla Barba, 1993). Although there is clear clinical evidence that confabulation is often part of the cognitive profile of AD patients, only a few studies have been devoted to this issue. In a recent study, Dalla Barba, Nedjam, and

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Dubois (1999) addressed the relationship between confabulation, source memory, and executive functions in AD patients. They used six tasks tapping executive functions; a task in which subjects had to distinguish the origin of given information, that is, visual perception or imagination; a modified version of the Confabulation Battery (Dalla Barba, 1993) tapping episodic memory; general semantics and personal plans; and a modified version of the Crovitz test, in which, in response to a cue word, subjects must produce a personal memory, a general semantic memory, or a personal plan. AD patients were clearly impaired on tests of executive functions and showed poor monitoring abilities for the source of information. AD patients confabulated when they were required to retrieve a personal episode and, although less frequently, when they were required to make a personal plan. Correlation studies showed that AD patients’ confabulation did not correlate with their performance on executive tasks or with their ability to distinguish the origin of information. The same pattern of performance with AD patients impaired not only in episodic retrieval but also in personal future planning task, was found in another study by Nedjam, Dalla Barba, and Pillon (2000). Accordingly, the authors suggested that confabulation reflects a pathological awareness of personal temporality. There is now considerable converging evidence that the phenomenal experience that accompanies recognition of a previously presented stimulus seems to take at least two distinct forms. Recognition can occur when the stimulus evokes some specific experience in which the stimulus was previously involved, or, alternatively, when the stimulus gives rise only to a feeling of familiarity without any recollective experience. These two kinds of conscious awareness can be measured in laboratory conditions by “remember” and “know” responses (Tulving, 1985). A “remember” response indicates that recognizing the stimulus brings back to mind some conscious recollection of its prior occurrence, whereas a “know” response indicates that recognizing the stimulus is not accompanied by any conscious recollection of its prior occurrence. Dalla Barba (1997) investigated the relationship between recognition memory and conscious experience in AD patients. The purpose of the experiments was to compare “remember” measures of conscious awareness in free recognition and forced-choice recognition memory for words and unfamiliar faces. The point of the experiments was to see whether AD patients’ performance might be associated with a decrease in the relative incidence of “remember” responses as compared to normal controls, and whether there was an effect of experimental material (words versus faces) on the recognition performance and on the recollective experience. In both experiments, AD patients produced significantly fewer correct responses and fewer “remember” responses for correctly recognized items than normal controls. By contrast, AD patients produced the same proportion of “know” responses to target items as normal controls in all recognition conditions, with the exception of forced-choice recognition of faces, in which they gave more “know” responses to target faces than normal controls. These results

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are consistent with the assumption that recognition memory may entail two processes, only one of which gives rise to conscious recollection, and suggest that an impairment of conscious recollection is responsible for the poor performance of AD patients in recognition memory. PD Many studies have shown that episodic memory is impaired in PD. It is generally agreed, however, that some nondemented PD patients have normal episodic memory as measured with standard recall and recognition tasks. There is also evidence, however, that even nondemented, high-functioning PD patients may exhibit episodic memory impairment. Mohr and coworkers (1990), for example, evaluated the profile and extent of cognitive deficits in PD patients of exceptional distinction, who continued to function successfully in leadership positions. While these patients showed relative preservation of verbal skills and higher executive function, they exhibited a significant reduction in episodic memory and visuospatial function. Even nondemented PD patients who have normal episodic memory can exhibit impairment on memory tests that are failed by patients with frontal lesions. Deficits can be observed in tasks of temporal order (Sagar, Sullivan, Gabrieli, Corkin, & Growdon, 1988), source memory (Taylor, Saint-Cyr, & Lang, 1986), selfordered pointing (Gotham, Brown, & Marsden, 1988), and recall relative to recognition (Taylor et al., 1986). HD Episodic memory deficits are not typical of the early stage of HD. However, as the disease progresses, the episodic memory deficit becomes evident. Unlike AD, episodic memory deficits in HD have been traced to a general retrieval disorder. In other words, HD patients appear to store and retain new information, and they exhibit difficulty in initiating systematic retrieval strategies on episodic memory recall tasks.

Conclusion The end of the second millennium has coincided with significant progress in the understanding of human memory. Indeed, the very idea that memory is not a unitary system but rather one that reflects the interaction of different memory systems represents the greatest achievement of the last 50 years of neuropsychological research on memory. Moreover, many of the neural correlates of different memory systems have been identified through the study of patients with brain lesions and, more recently, through the introduction of functional neuroimaging techniques. The study of memory in aging and age-related neurological diseases has certainly largely contributed to the understanding of the organization of human memory. Nevertheless much is

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still to be learned about memory systems and subsystems, particularly the rules and mechanisms of how different systems and subsystems interact. The study of normal aging and brain-damaged subjects will very likely help to find an answer to many of the open questions in the near future.

Note 1 Adapted from Handbook of neuropsychology (vol.6), Dalla Barba, G., & Rieu, D., “Differential effects of aging and age-related neurological diseases on memory systems and subsystems” (pp. 97–118). Copyright 2001, with permission from Elsevier.

References Albert, M. S., Heller, H. S., & Milberg, W. (1988). Changes in naming abilities with age. Psychology and Aging, 3, 173–178. American Psychiatric Association (1994). Diagnostic and statistical manual of mental disorders (4th ed). Washington, DC: American Psychiatric Association. Asso, D. (1969). WAIS scores in a group of Parkinson patients. British Journal of Psychiatry, 115, 555–556. Auricombe, S., Grossman, M., Carvell, S., Stern, M. B., & Hurtig, H. I. (1993). Verbal fluency deficits in Parkinson’s disease. Neuropsychology, 7, 182–192. Babcock, R. L., & Salthouse, T. A. (1991). Effects of increased processing demands on age differences in working memory. Psychology and Aging, 5, 421–428. Bäckman, L. (1991). Recognition memory across the adult life span: The role of prior knowledge. Memory and Cognition, 19, 63–71. Bäckman, L., Almkvist, O., Nyberg, L., & Andersson, J. (2000). Functional changes in brain activity during priming in Alzheimer’s disease. Journal of Cognitive Neuroscience, 12, 134–141. Baddeley, A. (1994). Working memory: The interface between memory and cognition. In D. L. Schacter & E. Tulving (Eds.), Memory systems (pp. 351–367). Cambridge, MA: MIT Press. Baddeley, A., Cocchini, G., Della Sala, S., Logie, R. H., & Spinnler, H. (1999). Working memory and vigilance: Evidence from normal aging and Alzheimer’s disease. Brain and Cognition, 41, 87–108. Baddeley, A., & Hitch, G. J. (1974). Working memory. In G. Bower (Ed.), Recent advances in learning and motivation (vol. 8, pp. 47–90). New York: Academic Press. Baddeley, A. D. (1986). Working memory. Oxford: Oxford University Press. Baddeley, A. D., Bressi, S., Della Sala, S., Logie, R., & Spinnler, H. (1991). The decline of working memory in Alzheimer’s disease. Brain, 114, 2521–2542. Baddeley, A. D., Logie, R., Bressi, S., Della Sala, S., & Spinnler, H. (1986). Dementia and working memory. Quarterly Journal of Experimental Psychology, 38A, 603–618. Bayles, K. A., Trosset, M. W., Tomoeda, C. K., Montgomery, E. B., & Wilson, J. (1993). Generative naming in Parkinson’s disease patients. Journal of Clinical and Experimental Neuropsychology, 15, 547–562. Belleville, S., Peretz, I., & Malenfant, D. (1996). Examination of the working memory components in normal aging and in dementia of the Alzheimer type. Neuropsychologia, 34, 195–207.

22. Effects of aging and dementia on memory

463

Bergson, H. (1896). Matière et mémoire. Paris: Alcan. Blonder, L. X., Gur, R. E., Gur, R. C., Sayjin, A. J., & Hurtig, H. I. (1989). Neuropsychological functioning in hemiparkinsonism. Brain and Cognition, 9, 244–257. Bondi, M. W., & Kaszniak, A. W. (1991). Implicit and explicit memory in Alzheimer’s disease and in Parkinson’s disease. Journal of Clinical and Experimental Neuropsychology, 13, 339–358. Brown, R. G., & Marsden, C. D. (1988). Internal versus external cues and the control of attention in Parkinson’s disease. Brain, 111, 323–345. Brown, R. G., & Marsden, C. D. (1991). Dual task performance and processing resources in normal subjects and patients with Parkinson’s disease. Brain, 114, 215–231. Burkart, M., Heun, R., & Benkert, O. (1998). Serial position effects in dementia of the Alzheimer type. Dementia and Geriatric Cognitive Disorders, 9, 130–136. Burke, D. M., & MacKay, D. G. (1997). Memory, language and aging. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 352, 1845–1856. Burke, D. M., McKay, D. G., Worthley, J. S., & Wade, E. (1991). On the tip of the tongue: What causes word finding failure in young and older adults? Journal of Memory and Language, 30, 542–579. Buschke, H., & Hinrichs, J. V. (1968). Controlled rehearsal and recall order in serial list retention. Journal of Experimental Psychology, 78, 502–509. Buschke, H., & Kintsch, W. (1970). Rehearsal strategies and the serial-position curve in immediate free recall of ordered items. Quarterly Journal of Experimental Psychology, 22, 347–352. Buschke, H., Kuslansky, G., Katz, M., Stewart, W. F., Sliwinski, M. J., Eckholdt, H. M., & Lipton, R. B. (1999). Screening for dementia with the Memory Impairment Screen. Neurology, 52, 231–238. Buschke, H., Sliwinski, M. J., Kuslansky, G., & Lipton, R. B. (1997). Diagnosis of early dementia by the double memory test: Encoding specificity improves diagnostic sensitivity and specificity. Neurology, 48, 989–997. Butters, N., Heindel, W. C., & Salmon, D. P. (1990). Dissociation of implicit memory in dementia: Neurological implications. Bulletin of the Psychonomic Society, 28, 359–366. Canavan, A. G. M., Passingham, R. E., Marsden, C. D., Quinn, N., & Polkey, C. E. (1989). The performance on learning tasks of patients in the early stage of Rakinson’s disease. Neuropsychologia, 27, 141–156. Caplan, D., & Waters, G. (1999). Verbal working memory and sentence comprehension. Behavioral and Brain Sciences, 22, 95–126. Cappa, S. F., Binetti, G., Pezzini, A., Padovani, A., Rozzini, L., & Trabucchi, M. (1998). Object and action naming in Alzheimer’s disease and frontotemporal dementia. Neurology, 50, 351–355. Cherry, B. J., Buckwalter, J. G., & Henderson, V. W. (1996). Memory span procedures in Alzheimer’s disease. Neuropsychology, 10, 286–293. Chertkow, H., & Bub, D. (1990). Semantic memory loss in dementia of the Alzheimer’s type. Brain, 113, 397–417. Chertkow, H., Bub, D., & Caplan, D. (1992). Constraining theories of semantic memory processing: Evidence from dementia. Cognitive Neuropsychology, 9, 327–365. Claparède, E. (1911). Recognition et moïté. Archives de Psychologie, 11, 79–90. Cohen, N. J., & Squire, L. R. (1980). Preserved learning and retention of

464

Dalla Barba, Boller, Rieu

pattern-analyzing skill in amnesia: Dissociation of knowing how and knowing that. Science, 210, 207–209. Collette, F., Van der Linden, M., Bechet, S., & Salmon, E. (1999). Phonological loop and central executive functioning in Alzheimer’s disease. Neuropsychologia, 37, 905–918. Corkin, S., Gabrieli, J. D. E., Stanger, B. Z., Mickel, S. F., Rosen, T. J., Sullivan, E. V., et al. (1986). Skill learning and priming in Alzheimer’s disease. Neurology, 36 (Suppl. 1), 296. Craik, F. I. M., Govoni, R., Naveh-Benjamin, M., & Anderson, N. D. (1996). The effect of divided attention on encoding and retrieval processes in human memory. Journal of Experimental Psychology: General, 125, 159–180. Craik, F. I. M., & Jennings, J. M. (1992). Human memory. In F. I. M. Craik & T. A. Salthouse (Eds.), The handbook of aging and cognition (pp. 51–110). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Craik, F. I. M., & Rabinowitz, J. C. (1984). Age differences in the acquisition and use of verbal information. In H. Bouma & D. G. Bouwhuis (Eds.), Attention and performance X (pp. 471–499). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Dalla Barba, G. (1993). Confabulation: Knowledge and recollective experience. Cognitive Neuropsychology, 10, 1–20. Dalla Barba, G. (1997). Recognition memory and recollective experience in Alzheimer’s disease. Memory, 5, 657–672. Dalla Barba, G. (2001). Beyond the memory trace paradox and the fallacy of the homunculus: A hypothesis concerning the relation between memory, consciousness and temporality. Journal of Consciousness Studies, 8, 51–78. Dalla Barba, G., & Goldblum, M.-C. (1996). The influence of semantic encoding on recognition memory in Alzheimer’s disease. Neuropsychologia, 34, 1181–1186. Dalla Barba, G., Nedjam, Z., & Dubois, B. (1999). Confabulation, executive functions and source memory in Alzheimer’s disease. Cognitive Neuropsychology, 16, 385–398. Dalla Barba, G., Parlato, V., Iavarone, A., & Boller, F. (1995). Anosognosia, intrusions and “frontal” functions in Alzheimer’s disease and depression. Neuropsychologia, 33, 247–259. Dalla Barba, G., & Wong, C. (1995). Encoding specificity and intrusions in Alzheimer’s disease and amnesia. Brain and Cognition, 27, 1–16. Dalrymple-Alford, J. C., Kalders, A. S., Jones, R. D., & Watson, R. W. (1994). A central executive deficit in patients with Parkinson’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 360–367. Dannenbaum, S. E., Parkinson, S. R., & Inman, V. W. (1988). Short-term forgetting: Comparisons between patients with dementia of the Alzheimer’s type, depressed and normal elderly. Cognitive Neuropsychology, 5, 213–233. Della Sala, S., Lorenzo, G. D., Giordano, A., & Spinnler, H. (1986). Is there a specific visuo-spatial impairment in parkinsonians? Journal of Neurology, Neurosurgery, and Psychiatry, 49, 1258–1265. De Renzi, E., & Vignolo, L. (1962). “The Token Test”: A sensitive test to detect receptive disturbances in aphasics. Brain, 85, 665–678. Deweer, B., Ergis, A. M., Fossati, P., Pillon, B., Boller, F., Agid, Y., et al. (1994). Explicit learning, procedural learning and lexical priming in Alzheimer’s disease. Cortex, 30, 113–126. Eslinger, P. J., & Damasio, A. R. (1986). Preserved motor learning in Alzheimer’s

22. Effects of aging and dementia on memory

465

disease: Implications for anatomy and behavior. Journal of Neuroscience, 6, 3006–3009. Fleischman, D. A., & Gabrieli, J. D. (1998). Repetition priming in normal aging and Alzheimer’s disease. Psychology and Aging, 13, 88–119. Fleischman, D. A., Gabrieli, J. D., Reminfer, S., Rinaldi, J. F. M., & Wilson, R. (1995). Conceptual priming in perceptual identification for patients with Alzheimer’s disease and a patient with rightoccipital lobectomy. Neuropsychology, 9, 187–197. Forstl, H., Besthorn, C., Burns, A., Geiger-Kabisch, C., Levy, R., & Sattel, A. (1994). Delusional misidentification in Alzheimer’s disease: A summary of clinical and biological aspects. Psychopathology, 27, 194–199. Fournet, N., Moreaud, O., Roulin, J. L., Naegele, B., & Pellat, J. (2000). Working memory function in Parkinson’s disease patients and the effect of the withdrawal of dopaminergic medication. Neuropsychology, 14, 247–253. Fuld, P. A., Katzman, R., Davies, P., & Terry, R. D. (1982). Intrusions as a sign of Alzheimer dementia: Chemical and pathological verification. Annals of Neurology, 11, 155–159. Fung, T. D., Chertkow, H., & Templeman, F. D. (2000). Pattern of semantic memory impairment in dementia of Alzheimer’s type. Brain and Cognition, 43, 200–205. Gabrieli, J. D. E. (1986). Differential effects of aging and age-related neurological diseases on memory subsystems of the brain. In F. Boller & J. Grafman (Eds.), Handbook of neuropsychology (vol. 5, pp. 149–166). Amsterdam: Elsevier. Gabrieli, J. D. E. (1993). Memory systems of the human brain: Dissociations among learning capacities in amnesia. Cambridge, MA: MIT Press. Gall, F. J. (1835). The influence of the brain on the form of the head (W. Lewis, Trans.). Boston: Marsh, Capen & Lyon. Goldblum, M.-C., Gomez, C.-M., Dalla Barba, G., Boller, F., Deweer, B., Hahn, V., & Dubois, B. (1998). The influence of semantic and perceptual encoding on recognition memory in Alzheimer’s disease. Neuropsychologia, 36, 717–729. Gotham, A. M., Brown, R. G., & Marsden, C. D. (1988). ‘Frontal’ cognitive function in patients with Parkinson’s disease ‘on’ and ‘off’ levodopa. Brain, 111, 299–321. Graf, P., Squire, L., & Mandler, G. (1984). The information that amnesic patients do not forget. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 164–178. Green, J. D., Baddeley, A., & Hodges, J. R. (1996). Analysis of the episodic memory deficit in early Alzheimer’s disease: Evidence from the doors and people test. Neuropsychologia, 34, 537–551. Grossi, D., Becker, J. T., Smith, C., & Trojano, L. (1993). Memory for visuo-spatial patterns in Alzheimer’s disease. Psychological Medicine, 23, 65–70. Growdon, J. H., & Corkin, S. (1986). Cognitive impairment in Parkinson’s disease. In M D. Yhar & K. J. Bergman (Eds.), Parkinson’s disease (Advances in Neurology, vol. 45). New York: Raven Press. Gurd, J., & Ward, C. (1989). Retrieval from semantic and letter-initial categories in patients with Parkinson’s disease. Neuropsychologia, 27, 743–746. Heindel, W. C., Butters, N., & Salmon, D. P. (1988). Impaired learning of a motor skill in patients with Huntington disease. Behavioral Neuroscience, 102, 141–147. Heindel, W. C., Salmon, D. P., & Butters, N. (1990). Pictorial priming and cued recall in Alzheimer’s disease and Huntington disease. Brain and Cognition, 13, 282–295. Heindel, W. C., Salmon, D. P., Shults, C. W., Walicke, P. A., & Butters, N. (1989).

466

Dalla Barba, Boller, Rieu

Neuropsychological evidence for multiple implicit memory systems: A comparison of Alzheimer’s, Huntington’s, and Parkinson’s disease patients. Journal of Neuroscience, 9, 582–587. Horn, S. (1974). Some psychological factors in parkinsonism. Journal of Neurology, Neurosurgery, and Psychiatry, 37, 27–31. Howard, L. A., Binks, M. G., Moore, A. P., & Playfer, J. R. (2000). The contribution of apraxic speech to working memory deficits in Parkinson’s disease. Brain and Language, 74, 269–288. Hulme, C., Lee, G., & Brown, G. D. A. (1993). Short-term memory impairment in Alzheimer-type dementia: Evidence for separable impairments of articulatory rehearsal and long-term memory. Neuropsychologia, 34, 161–172. Husserl, E. (1950). Ideen zur einen reinen Phänomenologie (G. Alliney, Trans.). Hen Haag: Martinus Nijhoff. Ivory, S. J., Knight, R. G., Longmore, B. E., & Caradoc-Davies, T. (1999). Verbal memory in non-demented patients with idiopathic Parkinson’s disease. Neuropsychologia, 37, 817–828. James, W. (1890). Principles of psychology. New York: Holt. Johansson, B., & Berg, S. (1989). The robustness of the terminal decline phenomenon: Longitudinal data from the digit-span memory test. Journal of Gerontology: Psychological Science, 44, 184–186. Knopman, D., & Nissen, M. J. (1991). Procedural learning is impaired in Huntington’s disease: Evidence from the serial reaction time task. Neuropsychologia, 29, 245–254. Knopman, D. S., & Nissen, M. J. (1987). Implicit learning in patients with probable Alzheimer’s disease. Neurology, 37, 784–788. Koivisto, M., Portin, R., & Rinne, J. O. (1996). Perceptual priming in Alzheimer’s and Parkinson’s diseases. Neuropsychologia, 34, 449–457. Kopelman, M. D. (1985). Rates of forgetting in Alzheimer-type dementia and Korsakoff’s syndrome. Neuropsychologia, 23, 623–638. Korsakoff, S. S. (1889). Étude médico-psychologique sur une forme des maladies de la mémoire. Revue Philosophique, 28, 501–530. Lange, K. W., Sahakian, B. J., Quinn, N. P., Marsden, C. D., & Robbins, T. W. (1995). Comparison of executive and visuospatial memory function in Huntington’s disease and dementia of Alzheimer type matched for degree of dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 58, 598–606. Lawrence, A. D., Sahakian, B. J., Hodges, J. R., Rosser, A. E., Lange, K. W., & Robbins, T. W. (1996). Executive and mnemonic functions in early Huntington’s disease. Brain, 119, 1633–1645. Lawrence, A. D., Watkins, L. H., Sahakian, B. J., Hodges, J. R., & Robbins, T. W. (2000). Visual object and visuospatial cognition in Huntington’s disease: Implications for information processing in corticostriatal circuits. Brain, 123, 1349–1364. Lees, A. J., & Smith, E. (1983). Cognitive deficit in the early stages of Parkinson’s disease. Brain, 106, 257–270. Lesser, R. (1976). Verbal and non-verbal memory components of the Token Test. Cortex, 14, 79–85. Light, L. L. (1992). The organization of memory in old age. In F. I. M. Craik & T. A. Salthouse (Eds.), The handbook of aging and cognition (pp. 111–165). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Light, L. L., & Singh, A. (1987). Implicit and explicit memory in young and older

22. Effects of aging and dementia on memory

467

adults. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13, 531–541. Light, L. L., Singh, A., & Capps, J. L. (1986). Dissociation of memory and awareness in young and older adults. Journal of Clinical and Experimental Neuropsychology, 8, 62–74. Maine de Biran (1929). The influence of habit on the faculty of thinking. Baltimore, MD: Williams & Wilkins. Mark, R. R., & Rugg, M. D. (1998). Age effects on brain activity associated with episodic memory retrieval. An electrophysiological study. Brain, 121, 861–873. Marsh, G. G., Markham, L. M., & Ansel, R. (1971). Levodopa’s awakening effect on patients with parkinsonism. Journal of Neurology, Neurosurgery, and Psychiatry, 34, 209–218. Martone, M., Butters, N., Payne, M., Becker, J. T., & Sax, D. S. (1984). Dissociation between skill learning and verbal recognition in amnesia and dementia. Archives of Neurology, 41, 965–970. Mattioli, F., Miozzo, A., Vignolo, L. A. (1999). Confabulation and delusional misidentification: A four year follow-up study. Cortex, 35, 413–422. Miller, E. (1972). Efficiency of encoding and the short-term memory defects in presenile dementia. Neuropsychologia, 10, 133–136. Mishkin, M., Malamut, B., & Bachevalier, J. (1984). Memories and habits: Two neural systems. In G. Lynch, J. L. McGaugh, & N. M. Weinberger (Eds.), Neurobiology of learning and memory (pp. 65–77). New York: Guilford Press. Mitchell, D. B., Brown, A. S., & Murphy, D. R. (1990). Dissociation between procedural and episodic memory: Effects of time and aging. Psychology and Aging, 5, 264–276. Mohr, E., Juncos, J., Cox, C., Litvan, I., Feido, P., & Chase, T. N. (1990). Selective deficit in cognition and memory in high-functioning parkinsonian patients. Journal of Neurology, Neurosurgery, and Psychiatry, 53, 603–606. Montanes, P., Goldblum, M.-C., & Boller, F. (1995). The naming impairment of living and nonliving items in Alzheimer’s disease. Journal of the International Neuropsychological Society, 1, 39–48. Montanes, P., Goldblum, M.-C., & Boller, F. (1996). Classification deficits in Alzheimer’s disease with special reference to living and non-living items. Brain and Language, 54, 335–358. Morris, R. G. (1984). Dementia and the functioning of the articolatory system. Cognitive Neuropsychology, 7, 143–157. Morris, R. G. (1987). The effect of concurrent articulation on memory span in Alzheimer type dementia. British Journal of Clinical Psychology, 26, 233–234. Naveh-Benjamin, M., Craik, F. I. M., Guez, J., & Dori, H. (1998). Effects of divided attention on encoding and retrieval processes in human memory: Further support for an asymmetry. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 1091–1104. Nedjam, Z., Dalla Barba, G., & Pillon, B. (2000). Confabulation in a patient with frontotemporal dementia and in a patient with Alzheimer’s disease. Cortex, 36, 561–577. Nicholas, M., Obler, L., Albert, M., & Goodglass, H. (1985). Lexical retrieval in healthy aging. Cortex, 21, 595–606. Norman, D. A., & Shallice, T. (1986). Attention to action: Willed and automatic control of behavior. Reprinted in revised form. In R. J. Davidson, G. E. Schwarz, &

468

Dalla Barba, Boller, Rieu

D. Shapiro (Eds.), Consciousness and self-regulation. Advances in research and theory (Vol. 4). New York: Plenum Press. Nyberg, L., Nilsson, L. G., Olofsson, U., & Backman, L. (1997). Effects of division of attention during encoding and retrieval on age differences in episodic memory. Experimental Aging Research, 23, 137–143. Obler, B. A. (1980). Narrative discourse style in elderly. In L. K. Obler & M. L. Albert (Eds.), Language and communication in the elderly (pp. 75–90). Lexington, MA: Heath. Obler, L. K., & Albert, M. L. (1985). Language skills across adulthood. In J. E. Birren & K. W. Schaie (Eds.), Handbook of the psychology of aging (pp. 463–473). New York: Van Nostrand Reinhold. Orsini, A., Trojano, L., Chiacchio, L., & Grossi, D. (1988). Immediate memory spans in dementia. Perceptual and Motor Skills, 67, 267–272. Palladino, P., & De Beni, R. (1999). Working memory in aging: Maintenance and suppression. Aging, 11, 301–306. Parkinson, S. R. (1982). Performance deficits in short-term memory tasks. In L. S. Cermak (Ed.), Human memory and amnesia (pp. 77–96). Hillsdale, NJ: Lawrence Erlbaum Associates Inc. Parkinson, S. R., Lindholm, J. M., & Inman, V. W. (1982). An analysis of age differences in immediate recall. Journal of Gerontology, 37, 425–431. Perry, R. J., Watson, P., & Hodges, J. R. (2000). The nature and staging of attention dysfunction in early (minimal and mild) Alzheimer’s disease: Relationship to episodic and semantic memory impairment. Neuropsychologia, 38, 252– 271. Piatt, A. L., Fields, J. A., Paolo, A. M., Koller, W. C., & Troster, A. I. (1999). Lexical, semantic, and action verbal fluency in Parkinson’s disease with and without dementia. Journal of Clinical and Experimental Neuropsychology, 21, 435–443. Pirozzolo, F. J., Hansch, E. C., Mortimer, J. A., Webster, D. D., & Kuskowski, M. A. (1982). Dementia in Parkinson’s disease: A neuropsychological analysis. Brain and Cognition, 1, 71–83. Portin, R., Laatu, S., Revonsuo, A., & Rinne, U. K. (2000). Impairment of semantic knowledge in Parkinson’s disease. Archives of Neurology, 57, 1338–1343. Pratt, M. W., Boyes, C., Robins, S., & Manchester, J. (1989). Telling tales: Aging, memory and the narrative cohesion of story retelling. Developmental Psychology, 25, 628–635. Randolph, C. (1991). Implicit, explicit, and semantic memory functions in Alzheimer’s disease and Huntington’s disease. Journal of Clinical and Experimental Neuropsychology, 13, 479–494. Rebok, G. W., Bylsma, F. W., Keyl, P. M., Brandt, J., & Folstein, S. E. (1995). Automobile driving in Huntington’s disease. Movement Disorders, 10, 778–787. Reuter-Lorenz, P. A., Jonides, J., Smith, E. E., Hartley, A., Miller, A., Marshuetz, C., & Koeppe, R. A. (2000). Age differences in the frontal lateralization of verbal and spatial working memory revealed by PET. Journal of Cognitive Neuroscience, 12, 174–187. Ribot, T. (1882). Les Maladies de la mémoire. Paris: Alcan. Robertson, C., Hazlewood, R., & Rawson, M. D. (1996). The effect of Parkinson’s disease on the capacity to generate information randomly. Neuropsychologia, 34, 1069–1078. Rohrer, D., Salmon, D. P., Wixted, J. T., & Paulsen, J. S. (1999). The disparate

22. Effects of aging and dementia on memory

469

effects of Alzheimer’s disease and Huntington’s disease on semantic memory. Neuropsychology, 13, 381–388. Sagar, H. J., Sullivan, E. V., Gabrieli, J. D. E., Corkin, S., & Growdon, J. H. (1988). Temporal ordering and short-term memory deficit in Parkinson’s disease. Brain, 111, 525–539. Salmon, D. P., Heindel, W. C., & Lange, K. L. (1999). Differential decline in word generation from phonemic and semantic categories during the course of Alzheimer’s disease: Implications for the integrity of semantic memory. Journal of the International Neuropsychological Society, 5, 692–703. Salmon, D. P., Shimamura, A. P., Butters, N., & Smith, S. (1988). Lexical and semantic priming deficits in patients with Alzheimer’s disease. Journal of Clinical and Experimental Neuropsychology, 10, 477–494. Sartre, J.-P. (1943). L’Être et le néant. Paris: Gallimard. Schacter, D., Cooper, L., & Delaney, S. (1990). Implicit memory for unfamilar objects depends on access to structural descriptions. Journal of Experimental Psychology: General, 119, 5–21. Schacter, D. L. (1990). Perceptual representation system and implicit memory: Toward a resolution of the multiple memory systems debate. In A. Diamond (Ed.), The development and neural bases of higher cognitive functions (pp. 543–571). New York: New York Academy of Sciences. Schacter, D. L. (1994). Priming and multiple memory systems: Perceptual mechanisms of implicit memory. In D. L. Schacter & E. Tulving (Eds.), Memory systems in 1994. Cambridge, MA: MIT Press. Schacter, D. L., Cooper, L. A., & Treadwell, J. (1993). Preserved priming of novel objects across size transformation in amnesic patients. Psychological Science, 4, 331–335. Schacter, D. L., & Tulving, E. (1994). What are the memory systems of 1994? In D. L. Schacter & E. Tulving (Eds.), Memory systems. Cambridge, MA: MIT Press. Schaie, K. W., & Labouvie-Vief, G. (1974). Generational and cohort-specific differences in adult cognitive functioning: A fourteen-year study of independent samples. Developmental Psychology, 10, 305–320. Scoville, W. B., & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions. Journal of Neurology, Neurosurgery, and Psychiatry, 20, 11–21. Sherry, D. F., & Schacter, D. L. (1987). The evolution of multiple memory systems. Psychological Review, 94, 439–454. Shimamura, A. P., Salmon, D. P., Squire, L. R., & Butters, N. (1987). Memory dysfunction and word priming in dementia and amnesia. Behavioral Neuroscience, 101, 347–351. Silveri, M. C., Daniele, A., Giustolisi, L., & Gainotti, G. (1991). Dissociation between knowledge of living and nonliving things in dementia of the Alzheimer type. Neurology, 41, 545–546. Spencer, W. D., & Raz, N. (1995). Differential effects of aging on memory for content and context: A meta-analysis. Psychology and Aging, 10, 527–539. Spinnler, H. (1999). Alzheimer’s disease: Neuropsychological defects according to topographical spreading of neuronal degeneration. In G. Denes & L. Pizzamiglio (Eds.), Handbook of clinical and experimental neuropsychology (pp. 699–746). Hove: Psychology Press. Spinnler, H., Della Sala, S., Bandera, R., & Baddeley, A. (1988). Dementia, ageing, and the structure of human memory. Cognitive Neuropsychology, 5, 193–211.

470

Dalla Barba, Boller, Rieu

Sprengelmeyer, R., Canavan, A. G., Lange, H. W., & Homberg, V. (1995). Associative learning in degenerative neostriatal disorders: Contrast in explicit and implicit remembering between Parkinson’s and Huntington’s diseases. Movement Disorders, 10, 51–65. Squire, L. (1987). Memory and brain. New York: Oxford University Press. Stern, Y., Mayeux, R., & Cote, L. (1984). Reaction time and vigilance in Parkinson’s disease. Archives of Neurology, 41, 1086–1089. Taylor, A. E., & Saint-Cyr, J. A. (1995). The neuropsychology of Parkinson’s disease. Brain and Cognition, 28, 281–296. Taylor, A. E., Saint-Cyr, J. A., & Lang, A. E. (1986). Frontal lobe dysfunction in Parkinson’s disease: The cortical focus of neostriatal outflow. Brain, 109, 845–883. Tippette, L. J., Grossman, M., & Farah, M. (1996). The semantic memory impairment of Alzheimer’s disease: Category-specific. Cortex, 32, 143–153. Tröster, A. I., & Fields, J. A. (1995). Frontal cognitive function and memory in Parkinson’s disease: Toward a distinction between prospective and declarative memory impairments? Behavioural Neurology, 8, 59–74. Tröster, A. I., Fields, J. A., Testa, J. A., Paul, R. H., Blanco, C. R., Hames, K. A., et al. (1998). Cortical and subcortical influences on clustering and switching in the performance of verbal fluency tasks. Neuropsychologia, 36, 295–304. Tulving, E. (1972). Episodic and semantic memory. In E. Tulving & W. Donaldson (Eds.), Organization of memory. New York: Academic Press. Tulving, E. (1983). Elements of episodic memory. Oxford: Oxford University Press. Tulving, E. (1984a). Multiple learning and memory systems. In K. J. Lagerspetz & P. Niemi (Eds.), Psychology in the 1990’s. Amsterdam: Elsevier. Tulving, E. (1984b). Précis of elements of episodic memory. Behavioral and Brain Science, 7, 223–268. Tulving, E. (1985). Memory and consciousness. Canadian Psychology, 26, 1–12. Tulving, E., & Schacter, D. (1990). Priming and human memory systems. Science, 247, 301–306. Warrington, E., & Weiskrantz, L. (1968). A new method of testing of long-term retention with special reference to amnesic patients. Nature, 217, 972–974. Warrington, E. K. (1975). The selective impairment of semantic memory. Quarterly Journal of Experimental Psychology, 27, 635–657. Warrington, E. K., & Weiskrantz, L. (1970). Amnesia: Consolidation or retrieval? Nature, 6, 628–630. West, R. (1999). Visual distraction, working memory, and aging. Memory and Cognition, 27, 1064–1072. Wheeler, M. A., Stuss, D. T., & Tulving, E. (1997). Toward a theory of episodic memory: The frontal lobes and autonoetic consciousness. Psychological Bulletin, 121, 331–354. Wilson, R. S., Bacon, L. D., Fox, J. H., & Kaszniak, A. W. (1983). Primary memory and secondary memory in dementia of the Alzheimer’s type. Journal of Clinical Neuropsychology, 5, 337–344. Wilson, R. S., Como, P. G., Garron, D. C., Klawans, H. L., Barr, A., & Klawans, D. (1987). Memory failure in Huntington’s disease. Journal of Clinical and Experimental Neuropsychology, 9, 147–154.

23 Semantic dementia The story so far Jonathan Knibb and John R. Hodges

The syndrome of semantic dementia (SD), relatively recently described, continues to enjoy a rapid growth in interest among clinicians and neuropsychologists. This chapter aims to give a concise overview of our current knowledge of the condition, as well as highlighting areas of controversy and active research. After giving a brief account of the historical context, we will begin by outlining the characteristic clinical features which suggest a diagnosis of SD. The following section will take a more detailed look at the deficits from a neuropsychological point of view, starting with the specifically languagerelated problems. We will then address the question of semantic deficits in non-verbal tasks, a controversial issue which has direct bearing on the place of SD among progressive aphasia and other dementia syndromes. Our knowledge of the localization of brain atrophy in SD has increased considerably with the recent development of increasingly sophisticated techniques of imaging analysis, and we will review the current state of the literature in this area. Finally, we will conclude by discussing the variety of post-mortem pathological findings in cases of SD, and the impact of these on its classification as a neurodegenerative disease.

Historical and clinical features Patients with the clinical syndrome of what we now call SD were recognized by Pick (Pick, 1904; Pick, Girling, & Berrios, 1997) and a number of other early behavioural neurologists. In more recent times, two streams of literature have converged: the first neuropsychological, with pioneering reports by Warrington (1975) and Schwartz, Marin, and Saffran (1979), and the second neurological, initiated by Mesulam’s seminal report in 1982 (Mesulam, 1982). We will very briefly review these early reports. In 1975, Warrington (1975) described three patients with visual associative agnosia, who could perceive the structural features of a visual stimulus, but their ability to recognize objects by sight was impaired—a rare but welldescribed syndrome in the context of discrete brain lesions. There were, however, two unusual aspects of Warrington’s patients. Firstly, their deficits had appeared gradually, and were presumed to be due to cerebral degenerative

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disease. Secondly, the patients showed parallel deficits on word comprehension tasks. Warrington suggested that the problem lay not in a failure to access information, but in a breakdown of conceptual knowledge itself, or to use Tulving’s term, “semantic memory” (Tulving, 1972, 1983). A number of subsequent studies of similar patients supported Warrington’s conclusions (McCarthy & Warrington, 1986; Schwartz et al., 1979; Schwartz, Saffran, & Marin, 1980). The idea that degenerative brain disease may present as isolated aphasia had been brought to prominence in the neurological literature by Mesulam (1982), who described five patients with insidious, typically presenile disturbance of language production, in the absence of other cognitive deficits. This began with anomia, progressed to involve reduced speech output, phonological errors, and sentence comprehension deficits, and culminated in mutism. A follow-up editorial in 1987 (Mesulam, 1987) introduced the term “primary progressive aphasia” (PPA), and this became the most widely accepted designation. The following year, Poeck and Luzzatti (1988) reported patients with fluent speech in the context of a progressive aphasic syndrome, but the connection with the psychological literature was first made by Snowden, Goulding, and Neary (1989). Their three patients were very similar to those reported by Warrington in 1975: they showed fluent and phonetically accurate speech with normal syntax and prosody, and, in fact, gave a superficial impression of intact language abilities. However, in place of words for specific items, they used generic, vague, or circumlocutory expressions, and eventually responded only with echolalia or stereotyped phrases. They had difficulty in understanding any but the most common words. Testing these patients further, Snowden and her colleagues found that the problems were not limited to the verbal domain, but that recognition of objects and people from pictures was also impaired. They concluded, like Warrington, that their patients were suffering from a “profound loss of semantic information”, and that the cases were sufficiently consistent to define a clinical syndrome, for which they coined the term “SD”. Our interest in Cambridge began in the early 1990s (Hodges, Patterson, Oxbury, & Funnell, 1992) with initial observations on five patients with the syndrome described by Warrington, Snowden, and others. Our interests have encompassed a fuller description of the neuropsychological, behavioural, imaging, and neuropathological changes associated with the syndrome. In addition, the study of patients with this amazing accident of nature has contributed considerably to understanding normal cognitive processes. The following description is based on our cumulative observations of more than 50 patients over almost 15 years. Loss of memory for words is the most frequent complaint, and anomia is a salient early feature, both in spontaneous speech and on confrontation testing. Superordinate terms such as “thing” are common, and semantically related word substitutions or circumlocution may occur. The anomia is paralleled by reduced fluency in generating items from a specified semantic category. The degree of comprehension

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impairment is often masked in conversation due to the plethora of clues to content apparent in questions such as “How did you get to the hospital today?” Comprehension of single words, whether written or spoken, is however, impaired. A feeling of familiarity may remain when the information associated with a word has been lost; this is sometimes manifested in a phenomenon which has been called “aliénation du mot” (Poeck & Luzzatti, 1988), in which the patient gives a response such as: “ ‘Hobby’, ‘hobby’ . . . I think I know what ‘hobby’ means . . . but I can’t remember.” This often contrasts strikingly with a preserved ability to parse complex syntactic structures such as centre-embedded relative clauses. Other aspects of spoken language are also preserved, notably syntax, phonology, and prosody. In our 1992 paper, we stated that non-verbal problem solving, perceptual and visuospatial abilities, working memory, and episodic memory were spared. This statement has, in general, stood the test of time, except that the position regarding episodic memory has become quite complicated and contentious; for a full review, see Hodges and Graham (2001) and Nestor, Graham, Bozeat, Simons, and Hodges (2002). In brief, patients show good autobiographical memory for personally experienced events that occurred in the preceding 2–5 years, although their recall of more distant events is poor. This finding has, however, been controversial, some groups substantiating this pattern of a reverse step function (Snowden, Griffiths, & Neary, 1996), and others disputing the finding (Ivanoiu, Cooper, Shanks, & Venneri, 2004; Moss, Kopelman, Cappelletti, de Mornay Davies, & Jaldow, 2003; Westmacott & Moscovitch, 2002). The status of anterograde episodic memory is also debated. Patients show excellent recognition memory for pictures as long as the target and probe items are identical, but a change in exemplar (from one sort of clock to another, say)—or even a viewpoint change of the same item—produces a dramatic decline in performance (Graham, Simons, Pratt, Patterson, & Hodges, 2000; Simons, Graham, Galton, Patterson, & Hodges, 2001). We have argued that patients with SD become totally dependent upon the perceptual features of items to perform recognition memory tasks. Word-based anterograde memory is universally poor, even in the very early stages of the disorder. This may reflect the semantic deficit, but there is also accumulating evidence to support a modality-specific verbal memory deficit (Graham, Patterson, Powis, Drake, & Hodges, 2002), in concordance with recent neuroimaging investigations showing left hippocampal atrophy (see below). Behavioural changes were noted in two of our 1992 patients (Hodges et al., 1992), and further studies have confirmed that these are a frequent feature of SD, either forming part of the presenting syndrome or appearing later in the illness (Bozeat, Gregory, Ralph, & Hodges, 2000a; Snowden et al., 2001; Thompson, Patterson, & Hodges, 2003). Examples include changes in eating habits, stereotyped or compulsive behaviours, distractibility, and irritability. These features are very similar to those seen in the frontal or behavioural variant of frontotemporal dementia (fvFTD); in fact, one study

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directly comparing SD with fvFTD in this respect found identical features (Bozeat et al., 2000a), although others have demonstrated subtle differences (Snowden et al., 2001). Naming and reading abilities The speech of patients with SD is often described as empty or lacking in content. The first sign of this is a contraction of vocabulary for the most specific, narrowly defined semantic categories, and the substitution either of more generic or basic-level words, or of coordinate terms from the same category. These features are reflected and amplified in performance on naming tests. As the disease progresses, the breadth and depth of the impairment both increase, and a wider range of categories is affected at increasingly high levels. This applies to verbs as well as nouns: for one patient, “come” and “do” were the preferred verbs (Hodges et al., 1992). In parallel with this, the ability to generate exemplars from a specified category diminishes. Because the deficit affects knowledge at a conceptual level, a patient who cannot name pictures of animals will also perform poorly when asked to give a name from a verbal description of the same animals, to produce a description from the name, or to produce animal names in a category fluency task. Performance is typically better on word generation from a given initial letter, a task which also engages working memory and executive functions but demands less semantic input. This dissociation between letter and category fluency tasks is characteristic of SD (Rogers, Ivanoiu, Patterson, & Hodges, 2006). A longitudinal study of naming errors (Hodges, Graham, & Patterson, 1995) in a single case (JL) showed that within-category coordinate errors were common initially, but these gradually gave way to words indicating broad categories (Table 23.1). Some of these were the usual category terms, such as “bird”, while others were basic-level terms from within the category. The latter were generally of high frequency and related to the category prototype: for example, all small animals and some birds were called “cat”, and “horse” was used for larger animals. In fact, the choice of label for a degenerating Table 23.1 Picture-naming performance of patient JL at 6-month intervals, showing the typical progression from within-category errors to high-level superordinate terms and cross-category errors Item

Time 1

Time 2

Time 3

Time 4

Elephant Swan Peacock Pear Lips Toothbrush Cigarette

  Duck    

Horse Bird Bird Apple  Brush Pipe

Horse Bird Cat Egg To eat Hold and rub A rod

Animal Animal Vehicle Food A hole Piece of rod Don’t know

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category is influenced by a number of variables. Word frequency is important, and a patient’s last remaining words are commonly those which were particularly frequent in that person’s premorbid speech (unpublished observations). JL retained the word “vehicle” at a late stage, and patient EP (Hodges et al., 1992) was able to speak of cups, glasses, and bottles only as “container”. In a multiple regression analysis of various candidate variables (Lambon Ralph, Graham, Ellis, & Hodges, 1998), object familiarity and average age of word acquisition (assessed in normal control subjects), as well as word frequency, were independently correlated with naming ability for each item. A familiarity effect has also been demonstrated on an individual level (Bozeat, Ralph, Patterson, & Hodges, 2002), in so far as patients are often able to name or show the use of their own personal objects at a stage when their knowledge of that item’s basic-level category has been degraded. This and similar effects have been described as “a regression from context-free meaning to . . . personal, context-dependent meaning” (Grossman, 2002), reinforcing the independence from context proposed for the semantic memory system. Surface dyslexia, a tendency to misread irregularly spelt words and produce regularization errors (such as pronouncing “pint” to rhyme with “mint”), has been noted in SD since the earliest reports (Hodges et al., 1992; Snowden et al., 1989; Warrington, 1975). It has been present in all of the 50 or so cases seen in Cambridge, although there are occasional reports of SD lacking surface dyslexia (Cipolotti & Warrington, 1995). The reason for this discrepancy is not readily apparent. Surface dyslexia is particularly salient in the English language, owing to the unusual degree of ambiguity and idiosyncrasy of English spelling (as is surface dysgraphia, owing to its redundancy), but analogous effects have been documented in Italian (Galante, Tralli, Zuffi, & Avanzi, 2000) and Japanese (Imura, 1943; Jibiki & Yamaguchi, 1993; Sasanuma & Monoi, 1975). The connection between surface dyslexia and the breakdown of semantic memory is, we have argued, not incidental or simply an effect of colocalization (Patterson & Hodges, 1992). There is an item-byitem association between spoken words which fail to be understood (for example, in a word-picture matching paradigm) and irregular written words which are read incorrectly (Graham, Hodges, & Patterson, 1994; Macoir & Bernier, 2002). According to the triangular model proposed by Seidenberg and McClelland (1989), links to semantics help to maintain both the integrity of phonological word forms (Knott, Patterson, & Hodges, 1997; Patterson, Graham, & Hodges, 1994) and the binding of these to orthographic word forms. This effect is particularly important for low-frequency words. Similar deficits are seen in forming the past tense of irregular verbs (Patterson, Lambon Ralph, Hodges, & McClelland, 2001); SD patients make regularization errors on low-frequency irregular items, perhaps because semantic connections are relied upon only for low-frequency words, while other mechanisms such as neighbour effects (minifamilies of phonologically similar verbs, such as “blow”, “throw”, and “know”) are sufficient for the more common items.

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Non-verbal semantics: SD and primary progressive aphasia From the earliest work on SD, it was recognized that the kernel of the syndrome was a degeneration of semantic memory, involving but not restricted to lexical semantics. The growth of the clinical literature concerning SD during the 1990s coincided with an increasing awareness of primary progressive aphasia (PPA) (Lund and Manchester Groups, 1994; Mesulam, 2001; Neary et al., 1998; Weintraub, Rubin, & Mesulam, 1990), and the relationship between the two has become a matter of considerable debate. A partial alignment with PPA has at times allowed the linguistic and non-linguistic aspects of SD to become separated, and has led to confusion over nosology and terminology. In addition, the tests commonly used in the clinical setting are those that tap semantic knowledge via language—confrontation naming, category fluency, word-definition tasks, word–picture matching, and so on. Purely non-verbal tests, such as the picture version of the Pyramids and Palm Trees Test (Howard & Patterson, 1992), and tests of auditory semantics and colour knowledge are more time-consuming and specialized, and have sometimes taken second place to verbal tests in the clinical literature. In his influential 2001 review, Mesulam described PPA as varying along a fluent– non-fluent axis, and characterized SD as a combination of fluent PPA with a separate visual associative agnosia (Mesulam, 2001). Since visual agnosia, even of the associative type, is regarded as a perceptual deficit, patients with SD cannot be said to have PPA by this group’s definition (Mesulam, 2001; Mesulam, Grossman, Hillis, Kertesz, & Weintraub, 2003; Weintraub et al., 1990). According to Mesulam, then, SD is not a type of PPA, but can perhaps be classified as a “PPA-plus syndrome”. This dual-deficit view has been accepted by some (Hillis, Oh, & Ken, 2004) but not all investigators (Figures 23.1A, 23.1B, and 23.1C). Kertesz and coworkers (Kertesz, Davidson, McCabe, Takagi, & Munoz, 2003; Kertesz & Munoz, 2003) see SD as a unitary disorder rather than as a coincidence of verbal and visual agnosia, and place it within a more broadly defined spectrum of PPA on the basis of a common progression from early word-finding problems to late mutism. This in turn is seen as part of a group of overlapping presentations of lobar atrophy, for which they have coined the term “Pick complex”. Grossman and Ash (2004) also characterize SD as a distinct manifestation of FTD, and divide PPA into three discrete syndromes of progressive non-fluent aphasia, progressive mixed aphasia, and SD. They agree that the features of SD are due to a disorder of semantic memory, although, finding that non-verbal semantic deficits are not universally present, they widen their diagnostic criteria to include cases lacking such deficits within their definition of SD. It should be noted that the three patients in Warrington’s original study (Warrington, 1975) were identified initially on the basis of “visual object agnosia”. These subjects performed normally on tests of visual perception, including object matching and figure-ground discrimination. Not only were

Figure 23.1A The relationship between progressive aphasia as a whole (PA), primary progressive aphasia (PPA), visual associative agnosia (VAA), and semantic dementia (SD), as proposed by Mesulam et al. (Mesulam, 1987, 2001; Mesulam et al., 2003). SD is identified either with the overlap of VAA and fluent PA, or with all fluent (P)PA. Pathology cuts across categories: 60% dementia lacking distinctive histology (DLDH) (including ubiquitin-positive tau-negative pathology), 20% typical Pick’s disease, and 20% atypical or coincidental Alzheimer’s disease.

Figure 23.1B The relationship between primary progressive aphasia (PPA), frontotemporal dementia (FTD) considered as a syndrome, motor neuron disease (MND), and corticobasal degeneration syndrome (CBDS), and the pathological findings associated with these: tau-positive inclusions, tau-negative ubiquitin-positive inclusions, or dementia lacking distinctive histology (DLDH), as proposed by Kertesz et al. (Kertesz et al., 2003; Kertesz & Munoz, 2003).

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Figure 23.1C The relationship between the syndromes of frontal variant frontotemporal dementia (fvFTD), progressive non-fluent aphasia (PNFA), and semantic dementia (SD) and the motor syndromes of motor neuron disease (MND), corticobasal degeneration (CBD), and progressive supranuclear palsy (PSP); and the relationship between these syndromes and the histopathological findings of Alzheimer’s disease (AD), tauopathies (tau), ubiquitin-positive tau-negative inclusion bodies (ubiq), and dementia lacking distinctive histology (DLDH), as proposed by Hodges et al. (see text for references).

semantic deficits found by both visual and verbal tests, but “auditory agnosia” was demonstrated in two of the cases, using meaningful environmental sounds. Moreover, the same characteristic pattern of preserved superordinate category information with degraded subordinate information was seen in each modality. We have replicated these findings in groups of SD patients selected on grounds of language impairment (Bozeat, Lambon Ralph, Patterson, Garrard, & Hodges, 2000b; Hodges et al., 1992)—that is, in fluent progressive aphasics—making coincidence an unlikely explanation. Still more challenging for the dual-deficit view is the observation of item consistency across modalities: for each patient, an item that has elicited an

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incorrect response on one test is more likely to do so on other tests. By regression analysis to control for potential confounders, item consistency has been demonstrated between verbal tasks, non-verbal picture-based tasks, and non-verbal environmental-sound tasks (Bozeat et al., 2000b). An account by which these findings are not due to a supramodal semantic deficit must explain how separate linguistic and perceptual impairments can affect the same groups of stimuli and spare others. One of the observations that may lead to the (erroneous) conclusion of preserved non-verbal semantics is the fairly common report by caregivers that SD subjects continue to use objects appropriately, even when the ability to name the same objects is impaired. This might be seen as evidence of a selective language deficit. Object use is complex, however, and supported by non-semantic abilities. We have shown (Hodges, Bozeat, Lambon Ralph, Patterson, & Spatt, 2000; Hodges, Spatt, & Patterson, 1999) that SD patients perform normally on a problem-solving task in which they are asked to select a novel tool and use it to achieve a specified result. The same subjects’ ability to use certain real tools was impaired, particularly on less familiar items and ones for which knowledge was degraded on verbal testing. The use of real tools and other objects may be supported by the same problem-solving skills that allowed the patients to use the novel tools. There is also the issue of socalled item affordance (Gibson, 1977), the way in which perceptual properties of man-made objects, both visual and sensorimotor, are associated systematically with their operation and function. For instance, the visual properties of a hammer guide, or afford, certain grips and actions. A similar argument may explain the common discrepancy between verbally and visually based tests of knowledge. Of all the types of information associated with a core concept, the lexical sign is the most arbitrary and independent of context (de Saussure, 1916). Visual form, by contrast, provides non-arbitrary, consistent cues to category membership: four legs and a head suggest an animal (recognition of the form of a part contributes to recognition of the whole), while a graspable handle suggests a tool manipulable by hand (recognition of the form of a part contributes to recognition of the function of the whole). No such “privileged access” or “privileged relationships” obtain in the case of word forms, and therefore these are particularly sensitive to mild disturbance of the semantic system. These effects have been proposed on theoretical grounds, and are supported by the results of computational modelling (Caramazza, Hillis, Rapp, & Romani, 1990; Lambon Ralph & Howard, 2000). Patients with SD show (by definition) deficits on tests of non-verbal semantic knowledge, although these may not be present on all tasks at first presentation. Occasionally, however, patients have been described who resemble SD patients in their linguistic behaviour, with anomia, comprehension deficits, and surface dyslexia without phonological errors or impairment of repetition, but do not show semantic deficits on non-verbal testing (Graham, Patterson, & Hodges, 1995; Papagno & Capitani, 2001). However, with follow-up over a number of years, all these

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patients have been seen to develop the full syndrome of SD. The reason for this heterogeneity in presentation is not clear, although the anomic presentation has been linked with atrophy confined to the dominant hemisphere (Lambon Ralph, McClelland, Patterson, Galton, & Hodges, 2001). Perhaps the most objective and theory-neutral way of relating SD and PPA is to say that while a descriptive label of “progressive aphasia” may be appropriate to some cases of SD when they are first seen, the presence or subsequent development of semantic deficits in other test modalities, and frequently of behavioural features, distances this group of patients from the prototype of PPA described by Mesulam (1982). Therefore, an important question in this context is whether non-fluent and fluent forms of PPA can be reliably distinguished, or whether a continuum of presentations exists. A recent study by our group (Knibb, Xuereb, Patterson, & Hodges, 2006) has begun to address the lack of direct empirical evidence relating to this issue. We reviewed the case notes and neuropathology of 38 consecutive referrals to the Cambridge memory clinic whose predominant deficit was a progressive aphasic syndrome of any sort, and coded each for a range of language deficits, as well as for behavioural and other cognitive features. A hierarchical cluster analysis of the cases, using only the variables characterizing the aphasia, suggested a division into two broad groups; these corresponded well to the syndromes of progressive non-fluent aphasia and SD. The classification of SD as a discrete syndrome seems to be justified, though the question of the usefulness of “primary progressive aphasia” as a superordinate diagnostic term remains open. Relationship to other dementia syndromes If the relationship of SD to progressive aphasia is controversial, its place in the classification of dementia as a whole enjoys more of a consensus, though some questions remain. It was clear from the first descriptions that SD constituted a syndrome distinct from the typical presentation of any known neurodegenerative disease. In particular, the relative preservation of episodic memory and visuospatial abilities distinguished it clearly from dementia of Alzheimer’s type (DAT), although side-by-side comparisons came only later (Kramer et al., 2003; Perry & Hodges, 2000). It is nonetheless interesting to compare the results of research into language impairments in Alzheimer’s disease (AD) during the 1980s with subsequent findings of similar studies in SD. For example, it was found that naming errors tended to be semantically related to the stimulus (Bayles & Tomoeda, 1983); that performance on naming, word comprehension, and category fluency tests declined in parallel, while superordinate knowledge was relatively preserved (Martin & Fedio, 1983); that low-frequency words were the first to be affected (Kirshner, Webb, & Kelly, 1984); that the pattern of language deficits was related to “transcortical sensory aphasia” but also to “semantic aphasia”, in terms of traditional classifications (Hier, Hagenlocker, & Shindler, 1985); and that there was item

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consistency between naming and comprehension tests (Huff, Corkin, & Growdon, 1986). These findings were generally agreed to be the consequence of a progressive impairment of semantic memory, albeit here in the context of global dementia. More recent work has shown that non-verbal semantic deficits are part of this pattern, but also that some patients with mild DAT perform well on all semantic tests (Hodges & Patterson, 1995). Despite these similarities, SD and DAT form well-defined, clinically separate syndromes and are usually not difficult to distinguish in practice, owing principally to the early impairment of episodic memory that dominates any semantic deficits in DAT. SD is now placed fairly uncontroversially within the spectrum of FTD, although the nosology of FTD itself is somewhat contentious. The first set of diagnostic criteria for FTD to mention SD explicitly (Neary et al., 1998) used the term “FTD” to refer specifically to the behavioural syndrome associated with frontal lobe atrophy, and included progressive non-fluent aphasia and SD alongside the frontal variant as three clinical varieties of circumscribed frontal and/or temporal lobar atrophy. In 2001, a work group in the USA (McKhann et al., 2001) preferred to lump these syndromes together, calling the whole group “FTD”, and treating SD as one way in which this may present. The classification of SD under the heading of FTD is based on two main considerations. One of these, as mentioned above, is the frequency of behavioural features in SD resembling those seen in FTD; perhaps more important, though, are the similarities in the distribution of atrophy across the cerebral cortex and the histopathological characteristics of the affected brain tissue. Distribution of atrophy in SD Early on, temporal lobe atrophy had been seen at post-mortem in cases diagnosed as language-predominant Pick’s disease (Cummings & Duchen, 1981), and Snowden et al.’s report confirmed this with structural and functional neuroimaging (Snowden et al., 1989). More recently, a number of studies have used volumetric analyses of magnetic resonance imaging (MRI) scans (Boxer et al., 2003; Chan et al., 2001; Galton et al., 2001; Gorno-Tempini et al., 2004; Mummery et al., 2000; Rosen et al., 2002) (or in one case, diffusion tensor morphometry (Studholme et al., 2004)) to explore the patterns of shrinkage of various brain areas in SD. The results do not agree perfectly, but clear patterns emerge. The greatest burden of pathology is borne by the temporal lobes (Figure 23.2). Atrophy is reliably found in the temporal pole, amygdala, and neocortical temporal gyri, especially inferior and middle, and fairly frequently in the parahippocampal gyrus and fusiform gyrus. In general, temporal lobe atrophy is more pronounced anteriorly than posteriorly. Contrary to earlier reports based on visual inspection of CT and/or MRI, recent quantitative studies have shown consistent hippocampal atrophy. This again involves particularly the anterior (rostral) segment, and marked left–right asymmetry is

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Figure 23.2 Magnetic resonance imaging scan showing predominantly left-sided temporal lobe atrophy in a typical case of semantic dementia.

usual, the left side being most typically affected (Gorno-Tempini et al., 2004; Rosen et al., 2002). In AD, by contrast, the atrophy is symmetrical and global with anterior and posterior regions equally involved. Asymmetrical atrophy seems to be the rule in FTD as a whole, in both the frontal and temporal lobes (Edwards-Lee et al., 1997). For each temporal region in SD, some of the reports cited above find atrophy on the left side only, while others find bilateral involvement—no region has been reported to undergo purely right-sided atrophy. In individual cases, however, preferential involvement of the right hemisphere is well described. Though this is considered unusual within the group of patients presenting with the SD syndrome, a study which selected FTD patients on the grounds of temporal lobe atrophy found equal numbers of left- and right-sided cases (Edwards-Lee et al., 1997). Right-sided atrophy in SD produces a distinctive clinical picture, with more prominent behavioural features, problems with face recognition and lack of insight, and less marked linguistic features (Edwards-Lee et al., 1997; Lambon Ralph et al., 2001; Thompson et al., 2003). Atrophy outside the temporal lobe has also been reported (Gorno-Tempini et al., 2004; Mummery et al., 2000; Rosen et al., 2002), primarily in the

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ventromedial prefrontal cortex and insula. However, correlations between regional atrophy and impairment on semantic tests are restricted to temporal areas, including temporal pole, fusiform gyrus, and inferior temporal gyrus (Galton et al., 2001; Mummery et al., 2000; Rosen et al., 2002; Williams, Nestor, & Hodges, 2005). These findings strengthen the hypothesis that the regions crucial to the breakdown of semantic memory in SD are within the temporal lobe; on the other hand, the observation of frontal atrophy helps to place SD within the scope of FTD. Neuropathological features Part of the difficulty in classifying FTD is that it can be viewed on three different, imperfectly correlated levels—as clinical syndromes, as patterns of regional atrophy, or as histopathological findings. Classifications based on each of these have been proposed. Of the current consensus criteria, one group takes lobar atrophy as the reference standard and works outward to delineate pathological causes and clinical effects (Neary et al., 1998), while another group recommends a clinical definition but suggests that a histopathological nosology would be more valid if reliable clinicopathological correlations can be made (McKhann et al., 2001). The situation with SD is a little simpler, as the canonical definition proposed by Hodges et al. (1992) has formed the basis of more recent criteria and has led to an almost universal approach to SD as an essentially clinical-neuropsychological syndrome. Although the appellation “temporal variant FTD” is occasionally used, this is, in general, used either alongside “SD” if intended as a synonym, or as a purely descriptive phrase if not. According to current knowledge, the pathologies underlying FTD may be summarized under five headings (Hodges & Miller, 2001). Pick’s disease, a term which in its broadest sense may refer to the whole spectrum of focal lobar atrophy, applies more narrowly to the finding of characteristic tau- and ubiquitin-positive neuronal inclusions (Pick bodies) and ballooned achromatic neurons (Pick cells). In this latter sense, it still accounts for a substantial proportion of FTD pathology. Tau-positive inclusions are also seen in familial forms of FTD, and in corticobasal degeneration (which enjoys a closer correlation with its pathological substrate, but may present as FTD). The association between motor neuron disease (MND) and FTD has been established for over 100 years, but has only recently been widely recognized (Bak, O’Donovan, Xuereb, Boniface, & Hodges, 2001; Hudson, 1981; Jackson, Lennox, & Lowe, 1996; Rossor, Revesz, Lantos, & Warrington, 2000). The characteristic feature here is the presence of ubiquitin-positive, tau-negative inclusions, especially numerous in the dentate fascia of the hippocampus. Peripheral and cognitive features may appear together, one after the other, or alone. Any of the FTD syndromes may be associated with this disorder, SD among them, although it is unusual to see clinical signs of MND in a patient with SD. Finally, some cases show the cortical

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spongiform degeneration and gliosis that is common to all the above, but lack immunohistochemical findings using current techniques. Such cases are usually labelled as “dementia lacking distinctive histology” (DLDH). A recent case from the Cambridge series adds a further dimension: JC presented at 53 years of age with the typical syndrome of SD, associated with left temporal lobe atrophy on MRI. He developed bulbar and limb signs of MND shortly before his death 7 years later. Surprisingly, ubiquitin-positive cytoplasmic inclusions were absent from the hippocampus and neocortex, but inclusions with the same morphological and immunohistochemical characteristics were found in neurons of the inferior olivary nucleus. Ubiquitin acts as a non-specific marker of intracellular constituents destined for breakdown, and it seems unlikely that it has a primary causal role in FTD–MND; the discovery of more specific immunological markers of these inclusions may well improve our understanding of the pathology of this condition. A systematic review of the literature to 1998 (Davies et al., 2005) found only 12 pathological reports of cases which conformed to the SD syndrome. Seven of these showed typical Pick’s disease with Pick bodies, and the other five were reported as DLDH. Until recently, however, routine staining for ubiquitin was not always undertaken—or its significance appreciated—and we cannot rule out the possibility that early cases reported as DLDH might represent the FTD–MND syndrome. Indeed, the next case to be reported (Schwarz, De Bleser, Poeck, & Weis, 1998) was headlined as DLDH (nonAlzheimer, non-Pick pathology), although in fact ubiquitin staining characteristic of the FTD–MND syndrome was demonstrated. Four recent series have increased the case numbers considerably. Odawara et al. (2003) examined 10 patients diagnosed as FTLD, three FTD and seven SD, and found a perfect clinicopathological correspondence: Pick body pathology was a universal finding in the FTD patients, while ubiquitin-positive pathology was present in all the SD patients. Shi et al. (2005) also found seven SD patients among 70 FTLD patients, of whom five had ubiquitin-positive pathology and the others had DLDH. Taniguchi et al. (2004) identified 55 consecutive cases of FTLD; in this case, the four SD patients all showed DLDH with no tau or ubiquitin positivity. Most recently, our collaborative study with the Sydney group (Davies et al., 2005) described 18 cases of SD, and found ubiquitin-positive pathology in 13 of these, alongside three cases with Pick’s disease and two with AD features. The evidence to date suggests that ubiquitin-positive, tau-negative FTLD pathology is fairly predictable in SD, but a variety of different substrates are found in a minority of cases, and further work is needed to explore the significance of this. These results are not easy to reconcile. One potential point of difference concerns the criteria on which cases were classified as SD: Odawara et al. (2003) used the Neary et al. (1998) criteria, Davies et al. (2005) used criteria based on the group’s experience, and Taniguchi et al. (2004) are not explicit about their criteria. However, groups who diagnose SD on a regular basis do not differ conspicuously in their concept of the syndrome. The difficulty

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is compounded by reports of SD cases showing the histopathology typically associated with AD. As mentioned above, semantic memory deficits are common in patients with the clinical syndrome of AD, but a more severe episodic memory impairment usually makes the diagnosis clear. However, in Cambridge, we have seen AD patients in whom a semantic memory deficit predominated (Galton, Patterson, Xuereb, & Hodges, 2000), and two others who received a definite diagnosis of SD in life (Davies et al., 2005), but whose pathological examination showed typical AD at a microscopic level, though the macroscopic appearances were of frontotemporal degeneration. Further work is clearly needed to explore the complex relationships between clinical syndromes, patterns of atrophy, and histopathological findings.

Conclusion Over the past 15 years, SD has emerged from the obscurity of occasional case reports and has been recognized as a well-defined clinical syndrome, though not without a certain degree of controversy. It is now widely recognized that progressive fluent aphasia is frequently the first manifestation of a more deeply rooted impairment of conceptual knowledge, although the balance of deficits on verbal and non-verbal tests varies from patient to patient. Although other conditions may affect semantic memory, such as AD and herpes encephalitis, the latter disorders also affect episodic memory and other cognitive systems. The purity of the SD syndrome provides a unique viewpoint from which to study the structure of human semantic knowledge, and its roles in language, memory, and cognition. Longitudinal assessment also affords the opportunity to study the disintegration of the semantic system over time. The sites of brain atrophy in SD are highly consistent between cases, and the underlying neuropathology is also fairly consistent, although a range of pathologies is seen in a few cases. Future research may establish links between pathology and clinical presentation, and new terms may arise to describe pathologically defined diseases within the FTD spectrum, but for the present it seems most profitable to use a clinical definition as a firm place to stand from which to explore the implications of this fascinating syndrome.

References Bak, T. H., O’Donovan, D. G., Xuereb, J. H., Boniface, S., & Hodges, J. R. (2001). Selective impairment of verb processing associated with pathological changes in Brodmann areas 44 and 45 in the motor neurone disease-dementia-aphasia syndrome. Brain, 124, 103–120. Bayles, K. A., & Tomoeda, C. K. (1983). Confrontation naming impairment in dementia. Brain and Language, 19, 98–114.

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Boxer, A. L., Rankin, K. P., Miller, B. L., Schuff, N., Weiner, M., Gorno-Tempini, M. L., et al. (2003). Cinguloparietal atrophy distinguishes Alzheimer disease from semantic dementia. Archives of Neurology, 60, 949–956. Bozeat, S., Gregory, C. A., Ralph, M. A., & Hodges, J. R. (2000a). Which neuropsychiatric and behavioural features distinguish frontal and temporal variants of frontotemporal dementia from Alzheimer’s disease? Journal of Neurology, Neurosurgery, and Psychiatry, 69, 178–186. Bozeat, S., Lambon Ralph, M. A., Patterson, K., Garrard, P., & Hodges, J. R. (2000b). Non-verbal semantic impairment in semantic dementia. Neuropsychologia, 38, 1207–1215. Bozeat, S., Ralph, M. A., Patterson, K., & Hodges, J. R. (2002). The influence of personal familiarity and context on object use in semantic dementia. Neurocase, 8, 127–134. Caramazza, A., Hillis, A. E., Rapp, B. C., & Romani, C. (1990). The multiple semantics hypothesis: Multiple confusions? Cognitive Neuropsychology, 7, 161–189. Chan, D., Fox, N. C., Scahill, R. I., Crum, W. R., Whitwell, J. L., Leschziner, G., et al. (2001). Patterns of temporal lobe atrophy in semantic dementia and Alzheimer’s disease. Annals of Neurology, 49, 433–442. Cipolotti, L., & Warrington, E. K. (1995). Semantic memory and reading abilities: A case report. Journal of International Neuropsychology Society, 1, 104–110. Cummings, J. L., & Duchen, L. W. (1981). Kluver–Bucy syndrome in Pick disease: Clinical and pathologic correlations. Neurology, 31, 1415–1422. Davies, R. R., Hodges, J. R., Kril, J. J., Patterson, K., Halliday, G. M., & Xuereb, J. H., (2005). The pathological basis of semantic dementia. Brain, 128, 1984–1995. de Saussure, F. (1916). Cours de linguistique générale. Paris: Payot. Edwards-Lee, T., et al. (1997). The temporal variant of frontotemporal dementia. Brain, 120, 1027–1040. Galante, E., Tralli, A., Zuffi, M., & Avanzi, S. (2000). Primary progressive aphasia: A patient with stress assignment impairment in reading aloud. Neurological Science, 21, 39–48. Galton, C. J., Patterson, K., Graham, K., Lambon Ralph, M. A., Williams, G., Antoun, N., et al. (2001). Differing patterns of temporal atrophy in Alzheimer’s disease and semantic dementia. Neurology, 57, 216–225. Galton, C. J., Patterson, K., Xuereb, J. H., & Hodges, J. R. (2000). Atypical and typical presentations of Alzheimer’s disease: A clinical, neuropsychological, neuroimaging and pathological study of 13 cases. Brain, 123, 484–498. Gibson, J. J. (1977). The theory of affordances. In R. E. Shaw & J. Bransford (Eds.), Perceiving, acting, and knowing. New York: Lawrence Erlbaum Associates, Inc. Gorno-Tempini, M. L., Dronkers, N. F., Rankin, K. P., Ogar, J. M., La Phengrasamy, B. A., Rosen, H. J., et al. (2004). Cognition and anatomy in three variants of primary progressive aphasia. Annals of Neurology, 55, 335–346. Graham, K. S., Hodges, J. R., & Patterson, K. (1994). The relationship between comprehension and oral reading in progressive fluent aphasia. Neuropsychologia, 32, 299–316. Graham, K. S., Patterson, K., & Hodges, J. R. (1995). Progressive pure anomia: Insufficient activation of phonology by meaning. Neurocase, 1, 25–38. Graham, K. S., Patterson, K., Powis, J., Drake, J., & Hodges, J. R. (2002). Multiple inputs to episodic memory: Words tell another story. Neuropsychology, 16, 380–389. Graham, K. S., Simons, J. S., Pratt, K. H., Patterson, K., & Hodges, J. R. (2000).

23. Semantic dementia

487

Insights from semantic dementia on the relationship between episodic and semantic memory. Neuropsychologia, 38, 313–324. Grossman, M. (2002). Frontotemporal dementia: A review. Journal of International Neuropsychology Society, 8, 566–583. Grossman, M., & Ash, S. (2004). Primary progressive aphasia: A review. Neurocase, 10, 3–18. Hier, D. B., Hagenlocker, K., & Shindler, A. G. (1985). Language disintegration in dementia: Effects of etiology and severity. Brain and Language, 25, 117–133. Hillis, A. E., Oh, S., & Ken, L. (2004). Deterioration of naming nouns versus verbs in primary progressive aphasia. Annals of Neurology, 55, 268–275. Hodges, J. R., Bozeat, S., Lambon Ralph, M. A., Patterson, K., & Spatt, J. (2000). The role of conceptual knowledge in object use: Evidence from semantic dementia. Brain, 123, 1913–1925. Hodges, J. R., & Graham, K. S. (2001). Episodic memory: Insights from semantic dementia. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 356, 1423–1434. Hodges, J. R., Graham, N., & Patterson, K. (1995). Charting the progression in semantic dementia: Implications for the organisation of semantic memory. Memory, 3, 463–495. Hodges, J. R., & Miller, B. (2001). The classification, genetics and neuropathology of frontotemporal dementia. Introduction to the special topic papers. I. Neurocase, 7, 31–35. Hodges, J. R., & Patterson, K. (1995). Is semantic memory consistently impaired early in the course of Alzheimer’s disease? Neuroanatomical and diagnostic implications. Neuropsychologia, 33, 441–459. Hodges, J. R., Patterson, K., Oxbury, S., & Funnell, E. (1992). Semantic dementia. Progressive fluent aphasia with temporal lobe atrophy. Brain, 115, 1783–1806. Hodges, J. R., Spatt, J., & Patterson, K. (1999). “What” and “how”: Evidence for the dissociation of object knowledge and mechanical problem-solving skills in the human brain. Proceedings of the National Academy of Sciences of the USA, 96, 9444–9448. Howard, D., & Patterson, K. (1992). Pyramids and Palm Trees: A test of semantic access from pictures and words. Bury St Edmunds: Thames Valley Test Company. Hudson, A. J. (1981). Amyotrophic lateral sclerosis and its association with dementia, parkinsonism and other neurological disorders: A review. Brain, 104, 217–247. Huff, F. J., Corkin, S., & Growdon, J. H. (1986). Semantic impairment and anomia in Alzheimer’s disease. Brain and Language, 28, 235–249. Imura, T. (1943). Aphasia: Characteristic symptoms in Japanese. Psychiatria et Neurologia Japonica, 47, 196–218. Ivanoiu, A., Cooper, J. M., Shanks, M. F., & Venneri, A. (2004). Retrieval of episodic and semantic autobiographical memories in early Alzheimer’s disease and semantic dementia. Cortex, 40, 173–175. Jackson, M., Lennox, G., & Lowe, J. (1996). Motor neurone disease-inclusion dementia. Neurodegeneration, 5, 339–350. Jibiki, I., & Yamaguchi, N. (1993). The Gogi (word-meaning) syndrome with impaired kanji processing: Alexia with agraphia. Brain and Language, 45, 61–69. Kertesz, A., Davidson, W., McCabe, P., Takagi, K., & Munoz, D. (2003). Primary progressive aphasia: Diagnosis, varieties, evolution. Journal of International Neuropsychology Society, 9, 710–719.

488

Knibb and Hodges

Kertesz, A., & Munoz, D. G. (2003). Primary progressive aphasia and Pick complex. Journal of Neurological Science, 206, 97–107. Kirshner, H. S., Webb, W. G., & Kelly, M. P. (1984). The naming disorder of dementia. Neuropsychologia, 22, 23–30. Knibb, J. A., Xuereb, J. H., Patterson, K., & Hodges, J. R. (2006). Clinical and pathological characterization of progressive aphasia. Annals of Neurology, 59, 156–165. Knott, R., Patterson, K., & Hodges, J. R. (1997). Lexical and semantic binding effects in short-term memory: Evidence from semantic dementia. Cognitive Neuropsychology, 14, 1165–1216. Kramer, J. H., Jurik, J., Sha, S. J., Rankin, K. P., Rosen, H. J., Johnson, J. K., et al. (2003). Distinctive neuropsychological patterns in frontotemporal dementia, semantic dementia, and Alzheimer disease. Cognitive and Behavioral Neurology, 16, 211–218. Lambon Ralph, M. A., Graham, K. S., Ellis, A. W., & Hodges, J. R. (1998). Naming in semantic dementia: What matters? Neuropsychologia, 36, 775–784. Lambon Ralph, M. A., & Howard, D. (2000). Gogi aphasia or semantic dementia? Simulating and assessing poor verbal comprehension in a case of progressive fluent aphasia. Cognitive Neuropsychology, 17, 436–465. Lambon Ralph, M. A., McClelland, J. L., Patterson, K., Galton, C. J., & Hodges, J. R. (2001). No right to speak? The relationship between object naming and semantic impairment: Neuropsychological evidence and a computational model. Journal of Cognitive Neuroscience, 13, 341–356. Lund and Manchester Groups. (1994). Clinical and neuropathological criteria for frontotemporal dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 416–418. Macoir, J., & Bernier, J. (2002). Is surface dysgraphia tied to semantic impairment? Evidence from a case of semantic dementia. Brain and Cognition, 48, 452–457. Martin, A., & Fedio, P. (1983). Word production and comprehension in Alzheimer’s disease: The breakdown of semantic knowledge. Brain and Language, 19, 124–141. McCarthy, R., & Warrington, E. K. (1986). Phonological reading: Phenomena and paradoxes. Cortex, 22, 359–380. McKhann, G. M., Albert, M. S., Grossman, M., Miller, B., Dickson, D., & Trojanowski, J. Q. (2001). Clinical and pathological diagnosis of frontotemporal dementia: Report of the Work Group on Frontotemporal Dementia and Pick’s Disease. Archives of Neurology, 58, 1803–1809. Mesulam, M. M. (1982). Slowly progressive aphasia without generalized dementia. Annals of Neurology, 11, 592–598. Mesulam, M. M. (1987). Primary progressive aphasia—differentiation from Alzheimer’s disease. Annals of Neurology, 22, 533–534. Mesulam, M. M. (2001). Primary progressive aphasia. Annals of Neurology, 49, 425–432. Mesulam, M. M., Grossman, M., Hillis, A., Kertesz, A., & Weintraub, S. (2003). The core and halo of primary progressive aphasia and semantic dementia. Annals of Neurology, 54 (Suppl. 5), S11–14. Moss, H. E., Kopelman, M. D., Cappelletti, M., de Mornay Davies, P., & Jaldow, E. (2003). Lost for words or loss of memories? Autobiographical memory in semantic dementia. Cognitive Neuropsychology, 20, 703–732. Mummery, C. J., Patterson, K., Price, C. J., Ashburner, J., Frackowiak, R. S., & Hodges, J. R. (2000). A voxel-based morphometry study of semantic dementia:

23. Semantic dementia

489

Relationship between temporal lobe atrophy and semantic memory. Annals of Neurology, 47, 36–45. Neary, D., Snowden, J. S., Gustafson, L., Passant, U., Stuss, D., Black, S., et al. (1998). Frontotemporal lobar degeneration: A consensus on clinical diagnostic criteria. Neurology, 51, 1546–1554. Nestor, P. J., Graham, K. S., Bozeat, S., Simons, J. S., & Hodges, J. R. (2002). Memory consolidation and the hippocampus: Further evidence from studies of autobiographical memory in semantic dementia and frontal variant frontotemporal dementia. Neuropsychologia, 40, 633–654. Odawara, T., Iseki, E., Kanai, A., Arai, T., Katsuragi, T., Hino, H., et al. (2003). Clinicopathological study of two subtypes of Pick’s disease in Japan. Dementia, Geriatric and Cognitive Disorders, 15, 19–25. Papagno, C., & Capitani, E. (2001). Slowly progressive aphasia: A four-year follow-up study. Neuropsychologia, 39, 678–686. Patterson, K., Graham, N., & Hodges, J. R. (1994). The impact of semantic memory loss on phonological representations. Journal of Cognitive Neuroscience, 6, 57–69. Patterson, K., & Hodges, J. R. (1992). Deterioration of word meaning: Implications for reading. Neuropsychologia, 30, 1025–1040. Patterson, K., Lambon Ralph, M. A., Hodges, J. R., & McClelland, J. L. (2001). Deficits in irregular past-tense verb morphology associated with degraded semantic knowledge. Neuropsychologia, 39, 709–724. Perry, R. J., & Hodges, J. R. (2000). Differentiating frontal and temporal variant frontotemporal dementia from Alzheimer’s disease. Neurology, 54, 2277–2284. Pick, A. (1904). Zur Symptomatologie der linksseitigen Schläfenlappenatrophie. Monatsschrift für Psychiatrie und Neurologie, 16, 378–388. Pick, A., Girling, D. M., & Berrios, G. E. (1997). On the symptomatology of left-sided temporal lobe atrophy. Classic Text No. 29 (Trans. and annotated by D. M. Girling and G. E. Berrios). Historical Psychiatry, 8, 149–159. Poeck, K., & Luzzatti, C. (1988). Slowly progressive aphasia in three patients. The problem of accompanying neuropsychological deficit. Brain, 111, 151–168. Rogers, T. T., Ivanoiu, A., Patterson, K., & Hodges, J. R. (2006). Semantic memory in Alzheimer’s disease and the frontotemporal dementias: A longitudinal study of 236 patients. Neuropsychology, 20, 319–335. Rosen, H. J., Gorno-Tempini, M. L., Goldman, W. P., Perry, R. J., Schuff, N., Weiner, M., et al. (2002). Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology, 58, 198–208. Rossor, M. N., Revesz, T., Lantos, P. L., & Warrington, E. K. (2000). Semantic dementia with ubiquitin-positive tau-negative inclusion bodies. Brain, 123, 267–276. Sasanuma, S., & Monoi, H. (1975). The syndrome of Gogi (word meaning) aphasia. Selective impairment of kanji processing. Neurology, 25, 627–632. Schwartz, M. F., Marin, O. S., & Saffran, E. M. (1979). Dissociations of language function in dementia: A case study. Brain and Language, 7, 277–306. Schwartz, M. F., Saffran, E. M., & Marin, O. S. M. (1980). Fractionating the reading process in dementia. In M. Coltheart (Ed.), Deep dyslexia (pp. 259–269). London: Routledge & Kegan-Paul. Schwarz, M., De Bleser, R., Poeck, K., & Weis, J. (1998). A case of primary progressive aphasia. A 14-year follow-up study with neuropathological findings. Brain, 121, 115–126.

490

Knibb and Hodges

Seidenberg, M. S., & McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychology Review, 96, 523–568. Shi, J., Shaw, C. L., Du Plessis, D., Richardson, A. M., Baily, K. L., Julien, C., et al. (2005). Histopathological changes underlying frontotemporal lobar degeneration with clinicopathological correlation. Acta Neuropathologica, 110, 501–512. Simons, J. S., Graham, K. S., Galton, C. J., Patterson, K., & Hodges, J. R. (2001). Semantic knowledge and episodic memory for faces in semantic dementia. Neuropsychology, 15, 101–114. Snowden, J. S., Bathgate, D., Varma, A., Blackshaw, A., Gibbons, Z. C., & Neary, D. (2001). Distinct behavioural profiles in frontotemporal dementia and semantic dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 70, 323–332. Snowden, J. S., Goulding, P. J., & Neary, D. (1989). Semantic dementia: A form of circumscribed cerebral atrophy. Behavioural Neurology, 2, 167–182. Snowden, J. S., Griffiths, H., & Neary, D. (1996). Semantic-episodic memory interactions in semantic dementia: Implications for retrograde memory function. Cognitive Neuropsychology, 13, 1101–1137. Studholme, C., et al. (2004). Deformation tensor morphometry of semantic dementia with quantitative validation. NeuroImage, 21, 1387–1398. Taniguchi, S., McDonagh, A. M., Pickering-Brown, S. M., Umeda, Y., Iwatsubo, T., Hasegawa, M., et al. (2004). The neuropathology of frontotemporal lobar degeneration with respect to the cytological and biochemical characteristics of tau protein. Neuropathology and Applied Neurobiology, 30, 1–18. Thompson, S. A., Patterson, K., & Hodges, J. R. (2003). Left/right asymmetry of atrophy in semantic dementia: Behavioral-cognitive implications. Neurology, 61, 1196–1203. Tulving, E. (1972). Episodic and semantic memory. In E. Tulving & W. Donaldson (Eds.), Organisation of memory (pp. 381–403). New York: Academic Press. Tulving, E. (1983). Elements of episodic memory. Oxford: Clarendon Press. Warrington, E. K. (1975). The selective impairment of semantic memory. Quarterly Journal of Experimental Psychology, 27, 635–657. Weintraub, S., Rubin, N. P., & Mesulam, M. M. (1990). Primary progressive aphasia. Longitudinal course, neuropsychological profile, and language features. Archives of Neurology, 47, 1329–1335. Westmacott, R., & Moscovitch, M. (2002). Temporally graded semantic memory loss in amnesia and semantic dementia: Further evidence for opposite gradients. Cognitive Neuropsychology, 19, 135–163. Williams, G., Nestor, P. J., & Hodges, J. R. (2005). The neural correlates of semantic and behavioural deficits in frontotemporal dementia. NeuroImage, 24, 1042–1051.

24 Frontal lobe dysfunction across diagnostic dementia categories Sebastiaan Engelborghs, Peter Mariën, and Peter P. De Deyn

With 18-month prevalence rates approaching 90%, behavioural and psychological signs and symptoms of dementia (BPSD) are highly prevalent (Steinberg et al., 2003). A major proportion of BPSD consists of frontal lobe symptoms. Frontal lobe symptoms are not confined to dementia disorders with frontal lobe involvement such as frontotemporal dementia (FTD). Indeed, compared with normal, age-matched control subjects, 72% of Alzheimer’s disease (AD) patients displayed apathy and 36% displayed disinhibition, both of which are typical frontal lobe symptoms (Mega, Cummings, Fiorello, & Gornbein, 1996). A prospective, longitudinal study showed that 39.8% of patients with mild cognitive impairment (MCI) presented with apathy and that the proportion of conversion from MCI to AD was significantly higher for MCI patients with apathy at baseline (Robert et al., 2006). Studying apathy in AD patients, Kuzis, Sabe, Tiberti, Dorrego, and Starkstein (1999) and Starkstein, Petracca, Chemerinski, and Kremer (2001) found associations with dysthymia and major depression as well as with memory deficits, frontal lobe-related cognitive deficits, and impairment in activities of daily living. There is substantial evidence from observational and neuroimaging studies that agitation, aggressiveness, psychosis, and aberrant motor behaviour are manifestations of frontal lobe dysfunction too (Hirono, Mega, Dinov, Mishkin, & Cummings, 2000; Mega et al., 2000a; Senanarong et al., 2004). A neuropathological study found increased burden of neurofibrillary tangles in several frontal lobe regions of AD patients displaying agitation, apathy, and aberrant motor behaviour compared to AD patients without these symptoms (Tekin et al., 2001). Given the prevalence rates of frequently occurring symptoms of presumably frontal lobe origin such as agitated behaviour (60%) and aberrant motor behaviour (38%) in AD (Mega et al., 1996), the role of frontal lobe dysfunction in the pathophysiology of BPSD might have been systematically underestimated. Besides their medical impact, BPSD and frontal lobe symptoms have a major socio-economic and psychosocial impact, as they significantly contribute to patient distress and caregiver burden. In addition, these clinical phenomena are associated with early nursing home placement and increased cost of care (Murman et al., 2002). Indeed, frequently occurring symptoms of

492 Engelborghs, Mariën, De Deyn presumably frontal lobe origin such as agitated and aggressive behaviour are common precipitants of nursing home placement, are associated with caregiver burden, and have a negative impact on cognitive status, functional status, rate of cognitive decline, and overall prognosis (Senanarong et al., 2004). It has been hypothesized that frontal lobe dysfunction might predispose AD patients to BPSD by exaggerating behavioural responses to coexisting psychopathology or environmental provocations (Senanarong et al., 2004). Moreover, frontal lobe symptoms have been reported to predict functional impairment (Boyle et al., 2003) and behavioural response to cholinesterase inhibitor therapy in AD (Mega et al., 2000b). Despite their clinical, behavioural, and neuropsychological importance, only a limited number of studies have systematically investigated frontal lobe symptoms or confined their scope of attention to some specific forms of frontal lobe features such as apathy. Moreover, as many studies were crosssectional, focused on dementia as a single nosological entity, or dealt only with (some specific forms of BPSD occurring in) AD, knowledge of profiles and clinical, behavioural, and neuropsychological correlates of frontal lobe features across diagnostic categories is still sparse, showing the need for a better behavioural characterization. Paucity of insight into the underlying pathophysiological mechanisms of BPSD and frontal lobe symptoms is reflected by the limited (selective) pharmacological treatment options, especially in relatively rare forms of dementia such as FTD and dementia with Lewy bodies (DLB). However, studying BPSD and frontal lobe symptoms requires appropriate and standardized behavioural assessment scales.

Behavioural assessment scales for dementia: low sensitivity for frontal lobe features The development of standardized behavioural assessment scales, such as the Behavioural Pathology in Alzheimer’s Disease Rating Scale (Behave-AD) (Reisberg et al., 1987), the Neuropsychiatric Inventory (NPI) (Cummings et al., 1994), the Cohen-Mansfield Agitation Inventory (CMAI) (CohenMansfield, Marx, & Rosenthal, 1989), and the Cornell Scale for Depression in Dementia (CSDD) (Alexopoulos, Abrams, Young, & Shamoian, 1988), resulted in growing interest in BPSD, which is reflected by an increasing number of studies dealing with BPSD since the late 1980s. The Behave-AD is a 25-item scale that measures behavioural symptoms in seven clusters (paranoid and delusional ideation, hallucinations, activity disturbances, aggressiveness, diurnal rhythm disturbances, affective disturbances, and anxieties/ phobias), scored on a 4-point scale of increasing severity (Reisberg et al., 1987). Besides a total score, a global rating score is provided. This BehaveAD global rating reflects the impact and the burden of the various behavioural disturbances on the caregiver. The NPI scores both the severity and frequency of the following behavioural disturbances: delusions, hallucinations, agitation, depression, anxiety, euphoria, apathy, disinhibition, irritability,

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aberrant motor behaviour, night-time behaviours, and appetite and eating disorders. The CMAI assesses 29 agitated behaviours on a 7-point scale of increasing frequency (Cohen-Mansfield et al., 1989). CMAI cluster scores include aggressive behaviour, physically non-aggressive behaviour, and verbally agitated behaviour; a total score is provided as well. The CSDD is a 19-item depression scale in which symptoms are rated according to a 3-point severity score: absent, mild, or intermittent and severe symptoms (Alexopoulos et al., 1988). Although the NPI includes frontal lobe symptoms such as apathy, aberrant motor behaviour, and disinhibition and can discriminate FTD from AD, correctly classifying 77% of the subjects included in a study by Levy, Miller, Cummings, Fairbanks, and Craig (1996), scales such as the Behave-AD, CMAI, and CSDD lack sensitivity for frontal lobe symptoms, as they have specifically been developed for AD. As was recently demonstrated via a cross-sectional analysis of behavioural data from a large, prospective Belgian study on BPSD (Engelborghs et al., 2004a, 2005, 2006a), the BehaveAD even underestimates BPSD in FTD patients. Patients with probable AD (n=170), FTD (n=28), mixed dementia (defined as probable AD with minor cerebrovascular disease (MXD)) (n=29), and DLB (n=21) were included in this cross-sectional analysis and were investigated by means of a battery of behavioural assessment scales (Behave-AD, CMAI, and CSDD). According to scores on the Mini-Mental State Examination (MMSE) (Folstein, Folstein, & McHugh, 1975), the Hierarchic Dementia Scale (HDS) (Demonet et al., 1990), and the Global Deterioration Scale (GDS) (Reisberg, Ferris, de Leon, & Crook, 1982), no differences in dementia severity were observed in comparing the different diagnostic categories with the AD patient group (Table 24.1). Considering all disease groups, BPSD were frequent, only 7% (17/248) of patients included not showing BPSD (Behave-AD total score of 0) (AD: n=12; MXD: n=1; FTD: n=3; DLB: n=1). Moreover, 59% (146/248) of the patients displayed moderate to severe BPSD defined as Behave-AD total scores of ≤8 (AD: n=99; MXD: n=9; FTD: n=7; DLB: n=10). Despite the fact that behavioural disturbances of frontal lobe origin are a core diagnostic feature of FTD, the latter diagnostic category had significantly lower BehaveAD total scores compared to AD patients. However, the Behave-AD global rating that reflects caregiver burden was not significantly different between AD and FTD patient groups (Table 24.2) (Engelborghs et al., 2005). The fact that frequently used behavioural assessment scales have limited sensitivity for frontal lobe features not only hampered the systematic study of frontal lobe symptoms in dementia but was also a drawback in daily clinical practice. Indeed, with the development of new treatments for AD that may not be efficacious in the treatment of FTD, there is an increasing need for early discrimination of FTD from AD. Moreover, a different prognostic profile of AD versus FTD strengthens the need for (early) differential diagnosis. Despite striking neuropsychological and behavioural differences between AD and FTD, NINCDS–ADRDA criteria (McKhann et al., 1984) failed to differentiate AD from FTD, as many FTD patients fulfil the NINCDS–ADRDA

170 60/110 79.9 ± 7.0 76.4 ± 7.8 3.5 ± 2.5 5.3 ± 0.9 13.4 ± 6.2 138.5 ± 30.2 25.2 ± 12.1 20.6 ± 11.3

NA NA F=19.3*** F=20.3*** F=1.5 F=2.8 F=0.4 F=3.1 F=10.0** F=1.1

n

Male/female

Age at inclusion (years)

Age at onset (years)

Disease duration (years)

Global Deterioration Scale (1–7)

MMSE score (/30)

Hierarchic Dementia Scale (/200)

Boston Naming Test (/ 60)

Verbal Fluency Task

24.2 ± 11.5

30.5 ± 12.9

160.3 ± 20.8

14.4 ± 8.0

5.3 ± 0.8

3.4 ± 2.5

77.9 ± 5.3

81.3 ± 5.2

12/17

29

MXD

20.4 ± 14.3

34.7 ± 14.2**

143.0 ± 30.5

13.8 ± 9.2

4.8 ± 1.2

4.5 ± 4.1

65.1 ± 10.6***

69.6 ± 10.9***

12/16

28

FTD

25.3 ± 10.8

41.1 ± 8.8***

146.3 ± 31.6

15.0 ± 8.3

5.2 ± 1.1

4.5 ± 3.8

70.3 ± 6.2**

74.8 ± 5.7**

14/7

21

DLB

Data are given as mean ± sd. Significant differences comparing each disease group with the AD group are indicated as follows: **p < .01; ***p < .001. For comparison of male-female ratios, chi-square statistics were used. For all other comparisons, one-way-ANOVA with post hoc Dunnett’s procedure was applied. NA=not applicable.

AD

ANOVA

Table 24.1 Demographic, clinical, and neuropsychological data

Table 24.2 Behavioural data ANOVA

AD (n=170)

MXD (n=29)

FTD (n=28)

DLB (n=21)

MFS Total score

F=21.4***

3.7±1.7

3.8±1.7

6.3±1.3*** 4.0±1.6

Behave-AD Delusions

F=5.3**

2.4±3.0

1.2±2.0

0.5±1.1** 2.8±3.6

Behave-AD Hallucinations

F=12.2***

0.5±1.2

0.3±0.8

0.4±1.3

Behave-AD Psychosis

F=7.3***

2.9±3.4

1.6±2.2

0.9±1.8** 4.9±4.8

Behave-AD Activity disturbances

F=4.5**

2.5±2.2

1.5±1.7

2.1±2.0

1.0±1.4**

Behave-AD Aggressiveness

F=2.4

3.1±2.9

2.7±2.8

2.0±2.0

1.7±2.4

Behave-AD Diurnal rhythm disturbances

F=1.3

0.5±0.8

0.3±0.6

0.4±0.6

0.3±0.6

Behave-AD F=2.3 Affective disturbances

0.9±1.2

0.7±1.1

0.5±0.9

1.4±1.7

Behave-AD Anxiety/phobias

F=1.4

0.6±1.3

0.3±0.8

0.3±0.8

0.9±1.3

Behave-AD Total score

F=4.3**

10.5±7.4

7.2±5.5

6.2±4.2** 10.4±8.3

Behave-AD Global score

F=0.6

1.5±0.8

1.4±0.8

1.3±0.9

1.5±0.7

CMAI Aggressive behaviour

F=2.0

12.8±6.6

12.2±4.9

10.5±1.3

10.7±1.9

CMAI Physically nonaggressive behaviour

F=3.9

20.0±8.4

16.0±4.8

18.7±7.5

15.6±5.3

CMAI Verbally agitated behaviour

F=0.5

13.7±6.9

14.0±7.0

12.1±4.4

13.8±6.9

CMAI Total score

F=2.2

46.6±16.9 42.2±11.3 41.3±10.5

Cornell Scale for Depression Total score

F=3.0

5.3±3.8

6.4±4.2

5.8±3.1

2.3±2.4***

40.0±12.1 7.8±3.4

Data are given as mean ± sd. Significant differences comparing behavioural data of each disease group with the AD group are indicated as follows: **p < .01; ***p < .001 (one-way-ANOVA with post hoc Dunnett’s procedure). NA=not applicable.

496

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criteria of AD (Varma et al., 1999). Although a combination of behavioural, neuropsychological, and physical findings was useful in distinguishing FTD from AD (Rosen et al., 2002), behavioural quantification appeared to be more sensitive than cognitive testing in discriminating FTD from AD (Kertesz, Davidson, McCabe, & Munoz, 2003). Our memory team therefore developed the Middelheim Frontality Score (MFS), a disease-long clinical and behavioural assessment tool that measures frontal lobe features (De Deyn et al., 2005).

Assessment of frontal lobe symptoms From observational studies (Gustafson, 1987; Lund and Manchester Groups, 1994; Neary et al., 1998), 10 items were selected for inclusion in the MFS as follows: (1) initially comparatively spared memory and spatial abilities that reflect the neurobehavioural onset of the disease; frequently occurring personality and behavioural changes such as (2) loss of insight and judgement; (3) disinhibition; (4) dietary hyperactivity (referring to overeating); (5) changes in sexual behaviour (hypersexuality as well as the more frequently occurring hyposexuality); (6) stereotyped behaviour (encompasses all kinds of stereotyped behaviour, both simple repetitive behaviours (can also be oral) and complex behavioural routines such as wandering); (7) impaired control of emotions, euphoria, or emotional bluntness; (8) aspontaneity; (9) speech disturbances such as stereotyped phrases, logorrhoea, echolalia, and mutism; and, finally, (10) restlessness (for a detailed description of MFS items, see the “Instructions for Administration and Scoring” in De Deyn et al., 2005). Each item is scored either 0 (absent) or 1 (present) yielding a total maximal score of 10. All items that the patient has displayed since disease onset are scored 1. Information is obtained by a clinician from an interview of the patients and their professional and/or main caregiver, clinical files, and behavioural observation. The rater uses a form listing all items to be addressed. For the interview, a series of prespecified questions are asked (for details, see the “Instructions for Administration and Scoring” in De Deyn et al., 2005). The MFS was validated by means of a study including patients with probable AD (n=400) and FTD (n=62) (De Deyn et al., 2005). Comparing mean total MFS scores, FTD patients (6.3±1.8) had significantly higher scores than AD patients (3.1±1.8) (RST: p < .001). Distribution of scores on individual MFS items was significantly different between both disease groups (χ2=76.2, p < .001). A moderately positive and highly significant correlation was shown between the total MFS score and FTD diagnosis (Spearman: r = 0.478, p < .0001). In accordance with the generally accepted criteria for diagnostic biological markers for AD (Ronald and Nancy Reagan Research Institute, 1998), one could assume that a sensitivity and specificity of at least 80% should be achieved for a cut-off score to reliably allow discriminating FTD from AD. Given the favourable values of both sensitivity and specificity, a total MFS score of 5 was chosen as discriminatory cut-off (Table 24.3). Applying this

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497

Table 24.3 Sensitivity and specificity of diagnosis FTD in function of each possible total MFS score Total MFS score

Sensitivity (%)

Specificity (%)

≤0

100

0

≤1

100

23.3

≤2

98.4

40.8

≤3

98.4

59.5

≤4

95.2

77.0

≤5

88.7

89.0

≤6

72.6

96.8

≤7

48.4

99.3

≤8

17.7

100

≤9

4.8

100

≤ 10

1.6

100

cut-off score, 85.9% and 76.6%, respectively, of clinically diagnosed FTD and AD patients were correctly classified, resulting in a specificity of 89.0% and a sensitivity of 88.7%. Intra- and interrater variability was calculated in a different study population by means of retest correlation, revealing moderate to strong positive correlations of high statistical significance. It was concluded that the MFS is a clinical and behavioural assessment scale that measures frontal lobe features and that was shown to reliably discriminate FTD from AD patients (De Deyn et al., 2005). Moreover, we previously showed that the total MFS score correlates with severity of bifrontal hypoperfusion on SPECT in FTD (Pickut et al., 1997). Several other test batteries that assess frontal lobe functions have been developed in other research centres. Some relied on neuropsychological and executive function deficits, whereas others combined behavioural and neuropsychological features. Using a discriminant model derived from the MMSE and the Executive Interview (EXIT), a bedside measure of executive function, Royall, Mahurin, and Cornell (1994) were able to discriminate AD from FTD patients with a sensitivity and specificity of 83% and 85%, respectively. Using component scores from the Addenbrooke’s Cognitive Examination, Mathuranath, Nestor, Berrios, Rakowicz, and Hodges (2000) developed the VLOM ratio ([verbal fluency plus language]/[orientation plus memory]). Although the authors defined two different cut-off scores in order to optimize sensitivity and specificity for discriminating AD from non-AD and FTD from non-FTD dementia, sensitivities remained below the 80% threshold with values of 75% and 58%, respectively. The Frontal Assessment Battery (FAB) is a short bedside cognitive and behavioural battery that accurately

498 Engelborghs, Mariën, De Deyn discriminates patients with frontal lobe dysfunction from normal controls (Dubois, Slachevsky, Litvan, & Pillon, 2000). The sensitivity and specificity of the FAB to differentiate FTD (n=26) from AD (n=64) were evaluated, correctly identifying 78.9% of patients (Slachevsky et al., 2004). In subgroups of mildly demented AD (n=24) and FTD (n=9) patients, the FAB differentiated FTD from AD patients with a sensitivity and specificity of 77% and 87%, respectively (Slachevsky et al., 2004). The Frontal Behavioural Inventory (FBI) is a caregiver assessment scale specifically designed to quantify the personality/behavioural disorder of FTD (Kertesz, Davidson, & Fow, 1997). Based on a validation study with a limited number of FTD patients (n=26), the FBI reliably discriminated FTD from AD and other dementias (Kertesz, Nadkarni, Davidson, & Thomas, 2000). As the FBI score is based on the patient’s behaviour at the moment of the interview, and as patients were included at the time of first diagnostic assessment, it cannot be ruled out that the discriminatory power of the FBI decreases with disease progression. Indeed, disease progression may introduce new behaviours (such as apathy in AD patients) and may also lead to the disappearance of other symptoms (such as disinhibition in FTD patients). However, a longitudinal study on the FBI in 52 FTD and 52 AD patients demonstrated the usefulness of behavioural quantification, which appeared to be more sensitive than cognitive testing in FTD (Kertesz et al., 2003). A possible drawback of the FBI is that it is entirely caregiver-based, possibly limiting its reliability in certain circumstances. Indeed, the MFS is a disease-long assessment scale and is based on both clinical observation and interview of caregivers, which are major advantages for the more objective assessment of frontal lobe features in patients with more advanced dementia.

Characterization of BPSD and frontal lobe features across diagnostic dementia categories By means of the MFS and a battery of behavioural assessment scales, frontal lobe features and their behavioural and cognitive correlates were characterized across diagnostic dementia categories (Engelborghs et al., 2006a). We therefore performed a cross-sectional analysis of behavioural and neuropsychological data from a large, prospective Belgian study on BPSD, including patients with probable AD (n=170), FTD (n=28), MXD (n=29), and DLB (n=21). The neuropsychological and behavioural data of included patients are summarized in Tables 24.1 and 24.2. All patient groups were at the moderate stages of dementia. Moreover, all diagnostic categories were matched with regard to dementia severity according to MMSE, HDS, and GDS scores (Table 24.1). Compared to AD patients, both FTD and DLB subjects had significantly higher scores on the Boston Naming Test (BNT), a highly sensitive tool to identify naming deficits and impaired word-retrieval capacities in a variety of neurodegenerative disorders (Kaplan, Goodglass, & Weintraub, 1983; Mariën, Mampaey, Vervaet, Saerens,

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& De Deyn, 1998). Although verbal fluency has been linked to frontal lobe functioning (Cummings, 1993), FTD and DLB patients had similar scores on a semantic verbal fluency task (VFT) to the AD patient group. With the exception of the MXD subjects, who were behaviourally comparable to AD patients, all disease groups presented with specific behavioural profiles (Table 24.2). Behavioural data demonstrated that psychosis, activity disturbances, and aggressiveness were among the highest behavioural test scores in AD and MXD patients, in agreement with other studies (Allen & Burns, 1995; Ballard, Gray, & Ayre, 1999; Finkel, 2001; Hirono et al., 1998a). The behavioural characteristics of FTD patients differed from those of the AD patient group, as they displayed fewer delusions and more frontal lobe symptoms, as was reflected by significantly higher MFS total scores. BehaveAD data showed that the psychosis cluster score (that is calculated by adding together the scores of the delusions and hallucinations clusters) is the highest rated cluster in DLB patients, in accordance with previous studies (McKeith, 2002). As mean scores on the Behave-AD cluster “hallucinations” were significantly lower in DLB patients treated with levodopa than in untreated patients, it was unlikely that hallucinations reported in this group were induced by levodopa. In correlating MFS total scores with neuropsychological test and behavioural assessment scale scores, the following significant observations were made (Table 24.4). In AD (and to a lesser extent in MXD), MFS total scores were negatively correlated with scores on the MMSE (Spearman: r = –.36, p < .001) and a VFT (Spearman: r = –.38, p < .001), and they were associated with increased severity and frequency of psychosis (Spearman: r = 0.24, p < .01), activity disturbances (Spearman: r = .44, p < .001), and aggressiveness (Spearman: r = .43, p < .001). In the DLB, MFS total scores were negatively correlated with MMSE scores (Spearman: r = –.50, p = .020). No significant associations were found in FTD patients. Which conclusions can be drawn from this correlation study? First, in AD (and to a lesser extent in MXD) patients, frontal lobe symptoms were associated with more pronounced cognitive deficits (of frontal origin). Second, in AD (and to a lesser extent in MXD) patients, frontal lobe symptoms were associated with increased severity and frequency of agitated and aggressive behaviour. The clinical relevance of these observations is very likely since these findings are based on two different behavioural assessment scales (Behave-AD and CMAI) and correction for type I statistical errors. Moreover, these findings confirm the results of a study by Senanarong et al. (2004), who suggested that agitation is of frontal lobe origin in AD. Frontal lobe symptoms were associated with psychosis in AD patients, in accordance with a SPECT study demonstrating disproportionate dysfunction of the frontal lobes and related subcortical and parietal structures in AD patients with psychosis (Mega et al., 2000a). Third, AD patients displaying frontal lobe features had higher scores on the CSDD. Whether or not the prevalence of depression is higher in AD patients displaying more frontal lobe dysfunction cannot be elucidated

r = 0.16 (–0.22, 0.50) r = 0.20 (–0.18, 0.53) r = 0.31 (–0.06, 0.61) r = 0.53** (0.21, 0.76)

r = –0.13 (–0.28, 0.02) r = –0.20 (–0.34, –0.05) r = –0.38*** (–0.50, –0.25) r = 0.24** (0.09, 0.38)

Hierarchic Dementia Scale (/200)

Boston Naming Test (/ 60)

Verbal Fluency Task

Global Deterioration Scale (1–7) r = 0.22 (–0.16, 0.55) r = 0.06 (–0.31, 0.42) r = 0.16 (–0.22, 0.50) r = 0.48 (0.14, 0.73)

r = 0.23** (0.08, 0.38) r = 0.05 (–0.10, 0.20) r = 0.24** (0.09, 0.38) r = 0.44*** (0.31, 0.56)

Behave-AD Delusions

Behave-AD Hallucinations

Behave-AD Psychosis

Behave-AD Activity disturbances

Behavioural assessment scales

r = –0.06 (–0.42, 0.31)

r = –0.36*** (–0.49, –0.23)

MXD (n=29)

MMSE score (/30)

Neuropsychological tests

AD (n=170)

r = 0.36 (–0.02, 0.65)

r = –0.15 (–0.50, 0.24)

r = –0.13 (–0.48, 0.26)

r = –0.02 (–0.39, 0.36)

r = 0.21 (–0.18, 0.55)

r = –0.12 (–0.47, 0.27)

r = 0.27 (–0.12, 0.59)

r = –0.09 (–0.45, 0.29)

r = –0.04 (–0.41, 0.34)

FTD (n=28)

Table 24.4 Correlations between MFS total scores and neuropsychological and behavioural data

r = 0.52 (0.11, 0.78)

r = 0.26 (–0.20, 0.63)

r = 0.14 (–0.31, 0.54)

r = 0.22 (–0.24, 0.60)

r = 0.37 (–0.07, 0.70)

r = –0.52 (–0.78, –0.11)

r = –0.20 (–0.58, 0.26)

r = –0.54 (–0.79, –0.14)

r = –0.50* (–0.77, –0.09)

DLB (n=21)

r = 0.11 (–0.27, 0.46) r = 0.18 (–0.20, 0.52) r = –0.10 (–0.45, 0.28) r = 0.54** (0.22, 0.77) r = 0.53** (0.21, 0.76) r = 0.39 (0.03, 0.66) r = 0.45 (0.10, 0.71) r = 0.48 (0.14, 0.73) r = 0.56** (0.25, 0.78) r = 0.31 (–0.06, 0.61)

r = 0.19 (0.04, 0.33) r = 0.15 (0, 0.29) r = 0.14 (–0.01, 0.29) r = 0.49*** (0.37, 0.60) r = 0.43*** (0.31, 0.55) r = 0.39*** (0.26, 0.51) r = 0.48*** (0.36, 0.59) r = 0.36*** (0.23, 0.49) r = 0.53*** (0.42, 0.64) r = 0.45*** (0.32, 0.57)

Behave-AD Diurnal rhythm disturbances

Behave-AD Affective disturbances

Behave-AD Anxiety/phobias

Behave-AD Total score

Behave-AD Global score

CMAI Aggressive behaviour

CMAI Physically non-aggressive behaviour

CMAI Verbally agitated behaviour

CMAI Total score

Cornell Scale for Depression Total score

r = –0.09 (–0.45, 0.29)

r = 0.22 (–0.17, 0.56)

r = –0.18 (–0.52, 0.21)

r = 0.43 (0.07, 0.70)

r = 0.10 (–0.29, 0.46)

r = 0.21 (–0.18, 0.55)

r = –0.04 (–0.41, 0.34)

r = –0.36 (–0.02, 0.65)

r = –0.10 (–0.46, 0.29)

r = –0.02 (–0.39, 0.36)

r = –0.08 (–0.44, 0.31)

r = 0.20 (–0.26, 0.58)

r = 0.48 (0.06, 0.76)

r = 0.30 (–0.15, 0.65)

r = 0.57 (0.19, 0.81)

r = 0.19 (–0.27, 0.58)

r = 0.22 (–0.24, 0.60)

r = 0.33 (–0.12, 0.66)

r = –0.01 (–0.44, 0.43)

r = –0.34 (–0.68, 0.11)

r = 0.30 (–0.15, 0.65)

r = 0.33 (–0.12, 0.66)

Correlation calculation was performed by Spearman rank order. Correlations remaining statistically significant following Bonferroni correction for multiple comparisons are indicated as follows: *p < .05; **p < .01; ***p < .001. 95% confidence intervals are represented between parentheses.

r = 0.37 (0, 0.65)

r = 0.43*** (0.31, 0.55)

Behave-AD Aggressiveness

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Engelborghs, Mariën, De Deyn

by the present data set, as there is substantial overlap between frontal lobe symptoms and symptoms of depression. Indeed, emotional bluntness (MFS item 7) is a core feature of both apathy and depression. Conflicting data have been published on frontal lobe involvement in the pathophysiology of depression in AD, as some studies found an association (Hirono et al., 1998b) whereas others did not (Kuzis et al., 1999). Fourth, none of the reported associations between frontal lobe symptoms and neuropsychological and behavioural features in AD (and MXD) were found in FTD patients. With the exception of lower MMSE and VFT scores in DLB patients displaying more frontal lobe symptoms, no significant associations were found in DLB patients either. How can these findings be explained? In AD, the convincing associations between frontal lobe symptoms and neuropsychological and behavioural characteristics might be explained by the distributional sequence of neuropathological hallmarks of AD that progressively involve the frontal lobe with disease progression (Bradley et al., 2002). Frontal lobe symptoms such as apathy, cognitive abilities such as verbal fluency, and neuropsychiatric symptoms such as depression have been attributed to disruption of the corticosubcortical circuits involving the basal ganglia and the frontal lobes (Cummings, 1993; Kuzis et al., 1999; Landes, Sperry, Strauss, & Geldmacher, 2001) and have been associated with orbitofrontal and anterior cingulate cortex neurofibrillary tangle burden (Tekin et al., 2001). Based on a SPECT study, which supports the view that frontal corticosubcortical circuits mediate cognitive, behavioural, and affective components of motivation, dopaminergic enhancement has been suggested as a therapy for apathy (Benoit, Clairet, Koulibaly, Darcourt, & Robert, 2004). Indeed, changed activities of ascending dopaminergic pathways that are known to modulate activities of frontal subcortical circuits might explain the reported associations between the dopaminergic neurotransmitter system and symptoms such as aggression and agitation (Engelborghs, Vloeberghs, Maertens, Marescau, & De Deyn, 2004b; Soderstrom, Blennow, Sjodin, & Forsman, 2003). Many associations found in the AD patient group did not reach the level of statistical significance in the MXD patient group despite the presence of several trends and a clear parallelism in cognitive and behavioural features comparing both patient groups. Although one cannot rule out that differences in neuropsychological and behavioural correlates of frontal lobe dysfunction between both patient groups are related to—however minor—cerebrovascular disease, it seems more likely that negative findings can be attributed to small MXD sample size and correction for type I statistical errors. The same holds true for the negative findings in DLB and FTD groups. Limited statistical power due to small sample sizes is reflected by wide 95% confidence intervals, as displayed in Table 24.4. Therefore, confirmation of these negative findings in extended study populations (preferably with follow-up allowing histopathological confirmation of clinical diagnoses) is warranted.

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How can behavioural assessment scales be used to study the pathophysiology of frontal lobe symptoms in dementia? Behavioural assessment scales, sensitive to frontal lobe features, are very useful tools to study the pathophysiological mechanisms underlying frontal lobe symptoms in dementia. As demonstrated in the previous section, quantified frontal lobe symptoms can be correlated with neuropsychological and behavioural features, thus contributing to a better characterization of frontal lobe dysfunction across diagnostic dementia categories. Behavioural assessment scales can also be used to study associations with neuropathological features such as neurofibrillary tangle burden (Tekin et al., 2001) or to investigate correlations with regional hypoperfusion or hypometabolism in functional neuroimaging studies (Hirono et al., 2000; Mega et al., 2000a; Pickut et al., 1997; Salmon et al., 2003; Talbot, Lloyd, Neary, & Testa, 1998; Vogel, Hasselbalch, Gade, Ziebell, & Waldemar, 2005). Magnetic resonance imaging (MRI) allows us to study the behavioural correlates of both regional functional (Rombouts et al., 2003) and structural abnormalities (Rosen et al., 2005; Varma et al., 2002; Whitwell, Anderson, Scahill, Rossor, & Fox, 2004; Williams, Nestor, & Hodges, 2005). Correlating quantified frontal lobe features with cerebrospinal fluid (CSF) neurotransmitter (metabolite) levels might increase our insight into the neurochemical mechanisms that take part in the aetiopathogenesis of frontal lobe dysfunction in dementia, and this might prove to be relevant to the development of new and more selective pharmacological treatment options. We recently demonstrated that the MFS total score is significantly correlated (Spearman: r = –.510, p = .037) with the ratio of the CSF level of the (nor)adrenergic metabolite MHPG to that of norepinephrine, reflecting the turnover of norepinephrine (unpublished data). We also found a significant correlation between the ratio of the CSF level of the serotonergic metabolite 5-hydroxyindoleacetic acid (5HIAA) to the dopaminergic metabolite homovanillic acid (HVA) (reflecting the inhibitory modulation of dopamine on the serotonergic neurotransmitter system) with aggression and agitation in FTD, but not in AD (Engelborghs, Vloeberghs, Maertens, Marescau, & De Deyn, 2004b). According to this association, the changed activity of ascending dopaminergic pathways that are known to modulate activities of frontal subcortical circuits, plays a role in the aetiopathogenesis of aggression and agitation (Engelborghs et al., 2004b; Soderstrom et al., 2003). Last but not least, behavioural assessment scales can be used in genetic association studies. In FTD patients, we thus identified “dose-dependent” effects of the apolipoprotein E (APOE) allele ε4 on the Behave-AD total and cluster aggressiveness scores in FTD patients (Engelborghs et al., 2006b). Possible associations of the functional catechol-O-methyltransferase (COMT) rs4680 (Val158Met) and dopamine receptor D3 (DRD3) rs6280 (Ser9Gly) polymorphisms with neuropsychiatric symptoms of dementia were investigated as well, showing that COMT and DRD3 are associated with agitated

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behaviour and frontal lobe symptoms in AD, MXD, and FTD (unpublished data). Associations between DRD3 and aspontaneity were found in AD, whereas in FTD and DLB patients, DRD3 are associated with stereotyped behaviour and tearfulness, respectively. Given the significant association with functional COMT and DRD3 polymorphisms, these data once more show the important role of the dopaminergic neurotransmitter system in the pathophysiology of agitated behaviour and frontal lobe symptoms across diagnostic dementia categories. Behavioural assessment scales such as the MFS have proved to be important in the phenotypic characterization of new gene mutations, such as the novel presenilin 1 mutation that was associated with Pick’s disease (Dermaut et al., 2004) or the mutations in progranulin causing ubiquitin-positive FTD linked to chromosome 17q21 (Cruts et al., 2006). Indeed, in analysis of the genes within a minimal candidate region from a Dutch family and a Belgian family with FTDU-17, mutations were discovered in the PRGN gene that encodes the growth factor progranulin (Cruts et al., 2006). Taken together, the study indicated that FTDU-17 is probably due to PRGN loss of function and highlighted the importance of progranulin for neuronal survival.

Conclusions A major proportion of the very frequently occurring BPSD consists of frontal lobe symptoms. As frontal lobe symptoms are not confined to dementia disorders with frontal lobe involvement such as FTD, the role of frontal lobe dysfunction in the pathophysiology of BPSD might have been systematically underestimated. The fact that frequently used behavioural assessment scales have limited sensitivity to frontal lobe features has hampered the systematic study of frontal lobe symptoms in dementia. Since the development of test batteries and scales that assess frontal lobe functions, such as the MFS—a clinical and behavioural assessment scale that measures frontal lobe features and that was shown to reliably discriminate FTD from AD patients—several studies investigating the role of frontal lobe dysfunction in dementia have been set up. These studies might help to unravel the pathophysiology of frontal lobe symptoms in dementia, and that might prove to be indispensable for the development of new and more selective pharmacological treatment options.

Acknowledgements This work was supported by the Special Research Fund of the University of Antwerp, the Institute Born-Bunge, the association between the Institute Born-Bunge and the University of Antwerp, the International Alzheimer Research Foundation (Stichting voor Alzheimer Onderzoek), the Medical Research Foundation Antwerp, Neurosearch Antwerp, the Thomas Riellaerts Research Fund, the Research Foundation–Flanders (FWO–F) (grant

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no. G.0127.07), and the Institute for Promotion of Innovation Through Science and Technology in Flanders (IWT–Vlaanderen). S.E. is a postdoctoral fellow of the FWO–F.

References Alexopoulos, G. S., Abrams, R. C., Young, R. C., & Shamoian, C. A. (1988). Cornell Scale for Depression in Dementia. Biological Psychiatry, 23, 271–284. Allen, N. H. P., & Burns, A. (1995). The noncognitive features of dementia. Review of Clinical Gerontology, 5, 57–75. Ballard, C., Gray, A., & Ayre, G. (1999). Psychotic symptoms, aggression and restlessness in dementia. Review of Neurology, 155, 44–52. Benoit, M., Clairet, S., Koulibaly, P. M., Darcourt, J., & Robert, P. H. (2004). Brain perfusion correlates of the apathy inventory dimensions of Alzheimer’s disease. International Journal of Geriatric Psychiatry, 19, 864–869. Boyle, P. A., Malloy, P. F., Salloway, S., Cahn-Weiner, D. A., Cohen, R., & Cummings, J. L. (2003). Executive dysfunction and apathy predict functional impairment in Alzheimer disease. American Journal of Geriatric Psychiatry, 11, 214–221. Bradley, K. M., O’Sullivan, V. T., Soper, N. D. W., Nagy, Z., King, E. M. F., Smith, A. D., et al. (2002). Cerebral perfusion SPET correlated with Braak pathological stage in Alzheimer’s disease. Brain, 125, 1772–1781. Cohen-Mansfield, J., Marx, M. S., & Rosenthal, A. S. (1989). A description of agitation in a nursing home. Journal of Gerontology, 44, M77–M84. Cruts, M., Gijselinck, I., van der Zee, J., Engelborghs, S., Wils, H., Pirici, D., et al. (2006). Null mutations in progranulin cause ubiquitin-positive frontotemporal dementia linked to chromosome 17q21. Nature, 442, 920–924. Cummings, J. L. (1993). Frontal-subcortical circuits and human behavior. Archives of Neurology, 50, 873–880. Cummings, J. L., Mega, M., Gray, K., Rosenberg-Thompson, S., Carusi, D. A., & Gornbein, J. (1994). The Neuropsychiatric Inventory: comprehensive assessment of psychopathology in dementia. Neurology, 44, 2308–2314. De Deyn, P. P., Engelborghs, S., Saerens, J., Goeman, J., Mariën, P., Maertens, K., et al. (2005). The Middelheim Frontality Score: A behavioural assessment scale that discriminates frontotemporal dementia from Alzheimer’s disease. International Journal of Geriatric Psychiatry, 20, 70–79. Demonet, J. F., Doyon B., Ousset, P. J., Puel, M., Mahagne, M. H., Cardebat, D., et al. (1990). Standardization of a modular and hierarchic cognitive evaluation scale applicable to dementia. A French version of the Hierarchic Dementia Scale. Review of Neurology, 146, 490–501. Dermaut, B., Kumar-Singh, S., Engelborghs, S., Theuns, J., Rademakers, R., Saerens, J., et al. (2004). A novel presenilin 1 mutation (Gly183Val) is associated with Pick’s disease in the absence of β-amyloid plaques. Annals of Neurology, 55, 617–626. Dubois, B., Slachevsky, A., Litvan, I., & Pillon, B. (2000). The FAB. A frontal assessment battery at bedside. Neurology, 55, 1621–1626. Engelborghs, S., Vloeberghs, E., Maertens, K., Mariën, P., Somers, N., Symons, A., et al. (2004a). Correlations between cognitive, behavioural and psychological findings

506

Engelborghs, Mariën, De Deyn

and levels of vitamin B12 and folate in patients with dementia: a prospective study. International Journal of Geriatric Psychiatry, 19, 365–370. Engelborghs, S., Vloeberghs, E., Maertens, K., Marescau, B., & De Deyn, P. P. (2004b). Evidence for an association between the CSF HVA:5–HIAA ratio and aggressiveness in patients with frontotemporal dementia but not in Alzheimer’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 75, 1080. Engelborghs, S., Maertens, K., Nagels, G., Vloeberghs, E., Mariën, P., Symons, A., et al. (2005). Neuropsychiatric symptoms of dementia. Cross-sectional analysis from a prospective, longitudinal Belgian study. International Journal of Geriatric Psychiatry, 20, 1028–1037. Engelborghs, S., Maertens, K., Mariën, P., Vloeberghs, E., Somers, N., Nagels, G., et al. (2006a). Behavioural and neuropsychological correlates of frontal lobe features in dementia. Psychological Medicine, 36, 1173–1182. Engelborghs, S., Dermaut, B., Mariën, P., Symons, A., Vloeberghs, E., Maertens, K., et al. (2006b). Dose dependent effect of APOE ε4 on behavioral symptoms in frontal lobe dementia patients. Neurobiology of Aging, 27, 285–292. Finkel, S. I. (2001). Behavioral and psychological symptoms of dementia. A current focus for clinicians, researchers and caregivers. Journal of Clinical Psychiatry, 62, 3–6. Folstein, M., Folstein, S., & McHugh, P. R. (1975). Mini-Mental State. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–196. Gustafson L. (1987). Frontal lobe degeneration of non-Alzheimer type. II. Clinical picture and differential diagnosis. Archives of Gerontology and Geriatrics, 6, 209– 223. Hirono, N., Mori, E., Yasuda, M., Ikejiri, Y., Imamura, T., Shimomura, T., et al. (1998a). Factors associated with psychotic symptoms in Alzheimer’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 64, 648–652. Hirono, N., Mori, E., Ishii, K., Ikejiri, Y., Imamura, T., Shimomura, T., et al. (1998b). Frontal lobe hypometabolism and depression in Alzheimer’s disease. Neurology, 50, 380–383. Hirono, N., Mega, M. S., Dinov, I. D., Mishkin, F., & Cummings, J. L. (2000). Left frontotemporal hypoperfusion is associated with aggression in patients with dementia. Archives of Neurology, 57, 861–866. Kaplan, E., Goodglass, H., & Weintraub, S. (1983). Boston Naming Test. Philadelphia: Lea & Febiger. Kertesz, A., Davidson, W., & Fow, H. (1997). Frontal Behavioral Inventory: Diagnostic criteria for frontal lobe dementia. Canadian Journal of Neurological Sciences, 24, 29–36. Kertesz, A., Nadkarni, N., Davidson, W., & Thomas, A. W. (2000). The Frontal Behavioral Inventory in the differential diagnosis of frontotemporal dementia. Journal of the International Neuropsychological Society, 6, 460–468. Kertesz, A., Davidson, W., McCabe, P., & Munoz, D. (2003). Behavioral quantitation is more sensitive than cognitive testing in frontotemporal dementia. Alzheimer Disease and Associated Disorders, 17, 223–229. Kuzis, G., Sabe, L., Tiberti, C., Dorrego, F., & Starkstein, S. E. (1999). Neuropsychological correlates of apathy and depression in patients with dementia. Neurology, 52, 1403–1407.

24. Frontal lobe dysfunction in dementia

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Landes, A. M., Sperry, S. D., Strauss, M. E., & Geldmacher, D. S. (2001). Apathy in Alzheimer’s disease. Journal of the American Geriatric Society, 49, 1700–1707. Levy, M. L., Miller, B. L., Cummings, J. L., Fairbanks, L. A., & Craig, A. (1996). Alzheimer disease and frontotemporal dementias. Behavioral distinctions. Archives of Neurology, 53, 687–690. Lund and Manchester Groups (1994). Clinical and neuropathological criteria for frontotemporal dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 416–418. Mariën, P., Mampaey, E., Vervaet, A., Saerens, J., & De Deyn. P. P. (1998). Normative data for the Boston Naming Test in native Dutch-speaking Belgian elderly. Brain and Language, 65, 447–467. Mathuranath, P. S., Nestor, P. J., Berrios, G. E., Rakowicz, W., & Hodges, J. R. (2000). A brief cognitive test battery to differentiate Alzheimer’s disease and frontotemporal dementia. Neurology, 55, 1613–1620. McKeith, I. G. (2002). Dementia with Lewy bodies. British Journal of Psychiatry, 180, 144–147. McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984). Clinical diagnosis of Alzheimer’s disease: Report of the NINCDS– ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology, 34, 939–944. Mega, M. S., Cummings, J. L., Fiorello, T., & Gornbein, J. (1996). The spectrum of behavioural changes in Alzheimer’s disease. Neurology, 46, 130–135. Mega, M. S., Lee, L., Dinov, I. D., Mishkin, F., Toga, A. W., & Cummings, J. L. (2000a). Cerebral correlates of psychotic symptoms in Alzheimer’s disease. Journal of Neurology, Neurosurgery, and Psychiatry, 69, 167–171. Mega, M. S., Dinov, I. D., Lee, L., O’Connor, S. M., Masterman, D. M., Wilen, B., et al. (2000b). Orbital and dorsolateral frontal perfusion defect associated with behavioural response to cholinesterase inhibitor therapy in Alzheimer’s disease. Journal of Neuropsychiatry and Clinical Neuroscience, 12, 209–218. Murman, D. L., Chen, Q., Powell, M. C., Kuo, S. B., Bradley, C. J., & Colenda, C. C. (2002). The incremental direct costs associated with behavioral symptoms in AD. Neurology, 59, 1721–1729. Neary, D., Snowden, J. S., Gustafson, L., Passant, U., Stuss, D., Black, S., et al. (1998). Frontotemporal lobar degeneration. A consensus on clinical diagnostic criteria. Neurology, 51, 1546–1554. Pickut, B. A., Saerens, J., Mariën, P., Borggreve, F., Goeman, J., Vandevivere, J., et al. (1997). Discriminative use of SPECT in frontal lobe-type dementia versus (senile) dementia of the Alzheimer’s type. Journal of Nuclear Medicine, 38, 929–934. Reisberg, B., Borenstein, J., Salob, S. P., Ferris, S. H., Franssen, E., & Georgotas, A. (1987). Behavioral symptoms in Alzheimer’s disease: Phenomenology and treatment. Journal of Clinical Psychiatry, 48 (Suppl. 5), 9–15. Reisberg, B., Ferris, S. H., de Leon, M. J., & Crook, T. (1982). The Global Deterioration Scale (GDS) for assessment of primary degenerative dementia. American Journal of Psychiatry, 139, 1136–1139. Robert, P. H., Berr, C., Volteau, M., Bertogliati, C., Benoit, M., Sarazin, M., et al. (2006). Apathy in patients with mild cognitive impairment and the risk of developing dementia of Alzheimer’s disease: A one-year follow-up study. Clinical Neurology and Neurosurgery, 108, 733–736. Rombouts, S. A., van Swieten, J. C., Pijnenburg, Y. A., Goekoop, R., Barkhof, F., &

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Scheltens, P. (2003). Loss of frontal MRI activation in early frontotemporal dementia compared to early AD. Neurology, 60, 1904–1908. Ronald and Nancy Reagan Research Institute of the Alzheimer’s Association and the National Institute on Aging Working Group (1998). Consensus Report of the Working Group on Molecular and Biochemical Markers for Alzheimer’s disease. Neurobiology and Aging, 19, 109–116. Rosen, H. J., Hartikainen, K. M., Jagust, W., Kramer, J. H., Reed, B. R., Cummings, J. L., et al. (2002). Utility of clinical criteria in differentiating frontotemporal lobar degeneration (FTLD) from AD. Neurology, 58, 1608–1615. Rosen, H. J., Allison, S. C., Schauer, G. F., Gorno-Tempini, M. L., Weiner, M. W., & Miller, B. L. (2005). Neuroanatomical correlates of behavioural disorders in dementia. Brain, 128, 2612–2625. Royall, D. R., Mahurin, R. K., & Cornell, J. (1994). Bedside assessment of frontal degeneration: Distinguishing Alzheimer’s disease from non-Alzheimer’s cortical dementia. Experimental Aging Research, 20, 95–103. Salmon, E., Garraux, G., Delbeuck, X., Collette, F., Kalbe, E., Zuendorf, G., et al. (2003). Predominant ventromedial frontopolar metabolic impairment in frontotemporal dementia. Neuroimage, 20, 435–440. Senanarong, V., Cummings, J. L., Fairbanks, L., Mega, M., Masterman, D. M., O’Connor, S. M., et al. (2004). Agitation in Alzheimer’s disease is a manifestation of frontal lobe dysfunction. Dementia and Geriatric Cognitive Disorders, 17, 14–20. Slachevsky, A., Villalpando, J. M., Sarazin, M., Hahn-Barma, V., Pillon, B., & Dubois, B. (2004). Frontal assessment battery and differential diagnosis of frontotemporal dementia and Alzheimer disease. Archives of Neurology, 61, 1104–1107. Soderstrom, H., Blennow, K., Sjodin, A.-K., & Forsman, A. (2003). New evidence for an association between the CSF HVA:5–HIAA ratio and psychopathic traits. Journal of Neurology, Neurosurgery, and Psychiatry, 74, 918–921. Starkstein, S. E., Petracca, G., Chemerinski, E., & Kremer, J. (2001). Syndromic validity of apathy in Alzheimer’s disease. American Journal of Psychiatry, 158, 872–877. Steinberg, M., Sheppard, J.-M., Tschanz, J. T., Norton, M. C., Steffens, D. C., Breitner, J. C. S., et al. (2003). The incidence of mental and behavioral disturbances in dementia: The Cache County Study. Journal of Neuropsychiatry and Clinical Neurosciences, 15, 340–345. Talbot, P. R., Lloyd, J. J., Neary, D., & Testa, H. J. (1998). A clinical role for 99mTcHMPAO SPECT in the investigation of dementia? Journal of Neurology, Neurosurgery, and Psychiatry, 64, 306–313. Tekin, S., Mega, M. S., Masterman, D. M., Chow, T., Garakian, J., Vinters, H. V., & Cummings, J. L. (2001). Orbitofrontal and anterior cingulate cortex neurofibrillary tangle burden is associated with agitation in Alzheimer disease. Annals of Neurology, 49, 355–361. Varma, A. R., Snowden, J. S., Lloyd, J. J., Talbot, P. R., Mann, D. M., & Neary, D. (1999). Evaluation of the NINCDS–ADRDA criteria in the differentiation of Alzheimer’s disease and frontotemporal dementia. Journal of Neurology, Neurosurgery, and Psychiatry, 66, 184–188. Varma, A. R., Adams, W., Lloyd, J. J., Carson, K. J., Snowden, J. S., Testa, H. J., et al. (2002). Diagnostic patterns of regional atrophy on MRI and regional cerebral blood flow change on SPECT in young onset patients with Alzheimer’s disease, frontotemporal dementia and vascular dementia. Acta Neurologica Scandinavica, 105, 261–269.

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Vogel, A., Hasselbalch, S. G., Gade, A., Ziebell, M., & Waldemar, G. (2005). Cognitive and functional neuroimaging correlate for anosognosia in mild cognitive impairment and Alzheimer’s disease. International Journal of Geriatric Psychiatry, 20, 238–246. Whitwell, J. L., Anderson, V. M., Scahill, R. I., Rossor, M. N., & Fox, N. C. (2004). Longitudinal patterns of regional change on volumetric MRI in frontotemporal lobar degeneration. Dementia and Geriatric Cognitive Disorders, 17, 307–310. Williams, G. B., Nestor, P. J., & Hodges, J. R. (2005). Neural correlates of semantic and behavioural deficits in frontotemporal dementia. NeuroImage, 24, 1042–1051.

SECTION VII

Concluding remarks

Concluding remarks Peter Mariën and Jubin Abutalebi

Cognitive and experimental neuropsychology illustrate the enormous growth and rapid expansion of neuroscience over the past decades. As illustrated by several chapters of Neuropsychological Research, clinical neuropsychological observations have for many years been a solid and unique source of information to improve our understanding of the neural basis of cognitive functions. This state of affairs has considerably changed in the last decades as neuroscience has implemented new scientific methods in the interdisciplinary approach to cognitive processing and its underlying neural substrates. This neurocognitive revolution has led to significant developments in the theoretical modelling of cognitive functions in normal subjects. At the same time, modern functional neuroimaging techniques have provided a range of new opportunities for the investigation of brain activity in normal subjects engaged in cognitive tasks. These recent advances, combined with major developments in the field of neurophysiology and experimental psychology, have played a crucial role in the establishment of a new and important field of investigation called cognitive neuroscience. The increasing body of new theoretical knowledge must be confronted, critically evaluated and integrated with the evidence from clinical neuropsychological observations and assessments. The authors of the various chapters have outlined how the present insights were arrived at by means of such an integrated, multidisciplinary approach. Many of the contributing authors of Neuropsychological Research have personally witnessed a number of substantial changes in the basic approach to neurocognitive issues: from the anatomoclinical method in times that may seem remote to the reader to the present application of modern and advanced brain-imaging techniques. Likewise, many of the contributing authors of Neuropsychological Research have been engaged in the development of cognitive theories. Apart from exciting technical innovations for measuring brain activity, the cognitive neuropsychological approach has replaced the traditional, taxonomic, neurological level of description of brain (dys)functions during the last decades. The cognitive neuropsychological approach emerged in the second half of the last century and reflects the important developments in the fields of cognitive psychology and cognitive science. In its approach to the study of cognitive disorders, cognitive

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neuropsychology is based on a careful analysis of the quantitative and qualitative aspects of cognitive impairments in individual patients. The results of this analysis are interpreted on the basis of models of normal processing, derived from experimental investigations in normal subjects. The main goal of this approach is theoretical, rather than clinical; that is, it is the refinement of the understanding of the normal functional architecture of cognition. However, as demonstrated in Neuropsychological Research, improved knowledge in “cognitive physiology” may provide a robust rationale for the development of new treatment strategies in rehabilitation settings from which patients with neurological damage should ultimately benefit. We hope that Neuropsychological Research fully demonstrates the intrinsic value of intensive and extensive, multidisciplinary collaboration within the field of cognitive neuroscience. Most of the contributors to Neuropsychological Research are colleagues, friends, and past students of Professor Luigi Amedeo Vignolo. The various scientific issues represented and the rich variety of viewpoints expressed in this book exemplify the scientific eclecticism that Luigi has always enthusiastically endorsed. The neuroscientific dimension that runs through Neuropsychological Research honours Luigi’s constant efforts to relate cognitive behaviour to neuroanatomy and principles of neural function. The commitment to rehabilitation expressed in this volume reflects Luigi’s strong concern to improve the quality of life of the neurologically impaired patients he has treated over many years.

Author index

Aboitiz, F. 127, 128, 131 Abrams, R. C. 492, 493 Abutalebi, J. 56, 63, 64, 66, 68, 142, 143, 144 Ackerly, S. S. 394, 397 Ackerman, N. 154 Ackerman, R. H. 420 Adair, J. C. 178, 317, 318, 320, 321 Adams, H. P. 309, 311, 312, 315, 317, 320 Adams, M. R. 195 Adams, W. 503 Adolphs, R. 420 Adriani, M. 275, 276 Aggleton, J. P. 41 Agid, Y. 386, 441, 442 Aglieri, R. 195 Agnetti, V. 413 Agostini, E. 174 Agster, K. M. 425 Aguirre, G. K. 60, 67, 415 Ahad, P. 38, 273 Ahadi, S. A. 338, 343 Aharon-Peretz, J. 393, 402 Ahlfors, S. P. 366 Ahmed, A. 347 Aithamon, B. 142 Akhavein, R. 215 Akshoomoff, N. 342 Alajouanine, T. 76 Alberoni, M. 308, 310 Albert, M. L. 141, 187, 188, 268, 269, 270, 271, 274, 275, 219, 453 Albert, M. S. 481, 483 Aldridge, V. J. 332, 365 Alexander, D. N. 274, 276 Alexander, G. E. 384 Alexander, M. P. 39, 138, 268, 269, 270, 271, 275, 315, 402, 420 Alexopoulos, G. S. 492, 493 Alfonso-Reese, L. A. 242 Alho, K. 366 Aliminosa, D. 210, 211, 213 Alivisatos, B. 36, 37, 39, 40, 384, 388, 407, 418 Allard, T. 268, 269, 270, 271, 275 Allen, N. H. P. 499

Allison, S. C. 503 Allison, T. 349, 350 Allport, D. A. 253 Almqvist, O. 446 Amaral, D. G. 41, 42, 413, 425 Amin, D. 392 Amunts, K. 31, 37 Andelmand, F. 96 Anderson, A. 422 Anderson, B. 127, 132 Anderson, J. M. 168 Anderson, J. R. 242 Anderson, N. D. 449 Anderson, S. W. 338, 380, 392, 397, 421 Anderson, V. M. 503 Andersson, J. 446 Andreiuolo, P. A. 171 Angerlergues, R. 205, 215 Angrilli, A. 41 Anllo-Vento, L. 353, 356, 364, 365 Annoni, J. M. 215, 219 Ansaldo, A. I. 105, 142, 143, 144 Ansel, R. 451 Ansquer, J. C. 296, 317 Antani, S. 401, 403 Antell, S. E. 201 Antonini, A. 56 Antoun, N. 481, 483 Apostolos, G. T. 163 Arai, T. 484 Archambault, F. S. 388 Arduino, L. S. 122 Arguin, M. 122, 189 Armony, J. L. 273 Arnell, K. M. 361, 364 Aron, A. P. 415, 426 Aronson, A. E. 186 Ash, S. 476 Ashburner, J. 481, 482, 483 Ashby, F. G. 203, 242 Assal, G. 186, 187, 188, 273, 275, 276, 277, 317 Asso, D. 450 Astington, J. 20 Aten, J. 148, 155

516

Author index

Aubert, C. 273 Auburtin, E. 75, 76 Auerbach, S. H. 268, 269, 270, 271, 275 Auricombe, S. 455 Avanzi, S. 475 Avila, L. 148, 154 Awh, E. 384 Ayotte, J. 188 Ayre, G. 499 Azuma, M. 38 Babaï, M. 97 Babcock, R. L. 448 Bachevalier, M. 440 Bäckman, L. 446, 457 Bacon, L. D. 449 Baddeley, A. D. 321, 417, 419, 420, 447, 449, 450, 451, 458 Bader, L. 243 Badre, D. 426 Bai, J. 128 Baier, B. 308, 310 Bailey, C. H. 429 Bailey, P. 25, 269 Baily, K. L. 484 Bainton, D. 148, 150 Bak, T. H. 483 Baker, J. R. 57 Balakrishman, J. D. 203 Balint, R. 255 Ballantyne, A. 272 Ballard, C. 499 Ballard, D. 418, 427 Ballinger, W. E. 174 Balota, D. A. 35, 36 Bandera, R. 449 Bandettini, B. S. 172 Bandettini, P. A. 57, 288 Barat, M. 140 Barbas, H. 41, 382, 384 Barbizet, J. 296, 317 Barch, D. M. 337, 419 Bard, C. 188, 192 Barker, P. B. 310 Barkhof, F. 503 Barnes, C. L. 40 Baron, J. C. 138, 277, 310, 311, 313 Baron-Cohen, S. 402 Barr, A. 451 Barresi, B. 153 Barrett, A. M. 173 Barrouillet, P. 220 Barry, M. 96 Bartha, L. 67, 213 Basili, A. 206 Basso, A. 148, 154, 170, 171, 173, 174, 188, 307 Basso, G. 215 Bastiaansen, M. C. 366 Bastian, H. C. 79, 81

Bates, D. 268, 274, 277 Bates, J. F. 32, 38, 318 Bathgate, D. 473, 474 Bauer, R. M. 293, 420 Baunez, C. 317 Bavelier, D. 40 Baxter, D. M. 122 Baxter, M. G. 425 Bay, E. 250, 294 Bayles, K. A. 455, 480 Bayley, J. 411 Baylis, G. C. 35, 273 Bazin, C. 267 Bear, D. 268, 270, 271 Beauchamp, N. J. 310 Beauregard, M. 337 Beauvois, M. F. 123, 238, 241, 295 Bechara, A. 392, 397, 421 Bechet, S. 450 Beck, D. 252 Becker, J. T. 443, 450 Bedard, L. 420 Bedi, G. 271 Beeman, M. 99 Behrens, T. E. J. 26, 217 Beig, S. 427 Belin, P. 38, 141, 187, 273 Bell, W. L. 272 Belleville, S. 188, 449, 450 Bellmann, A. 275, 276 Bellmann Thiran, A. 276 Benasich, A. A. 130 Bender, M. 250 Benenson, M. 148 Benes, F. 342 Benevento, L. A. 35 Benke, T. 149, 213, 214 Benkert, O. 458 Benoit, M. 491, 502 Benson, D. A. 38, 86 Benson, D. F. 205, 250, 254, 255, 260, 274, 276, 380, 482 Benti, R. 56 Bentin, S. 361 Benton, A. 52, 269, 274, 275, 379, 380, 394, 397 Berg, S. 448 Berger, B. D. 393, 402 Berger, H. 205, 349, 350 Berger, M. S. 131, 133 Bergeson, T. R. 185, 186 Bergquist, T. F. 149 Bergson, H. 437 Berman, J. I. 131, 133 Berndt, R. S. 232, 243 Bernier, J. 475 Berns, G. 58 Bernstein, L. J. 427 Berr, C. 491 Berrios, G. E. 461, 497

Author index Berti, A. 308, 317, 320, 321 Bertogliati, C. 491 Bertrand, C. 308, 311 Bertrand, O. 366 Besson, M. 311 Besthorn, C. 459 Bhogal, S. K. 155 Bianchi, F. 148, 154 Bichot, N. P. 364 Biddle, K. R. 388 Bier, D. 139, 140 Biffi, S. 322n1 Bihrle, A. M. 97, 98 Binder, J. R. 172, 273, 288 Binet, A. 18 Binetti, G. 454 Binkofski, F. 171, 289, 290 Binks, N. G. 451 Birbaumer, M. 366 Birch, J. 253 Bird, C. M. 313 Birdsong, D. 64 Bisiacchi, P. 237, 243 Bisiach, E. 307, 308, 315, 317, 320, 321 Black, S. 269, 309, 310, 312, 317, 342, 394, 400, 476, 481, 483, 484, 496 Blackshaw, A. 473, 474 Blair, R. J. R. 338 Blaser, E. 352 Blasi, V. 142 Blatt, G. J. 42 Blennow, K. 502, 503 Block, E. 215 Blonder, L. X. 450 Bloomer, R. H. 388 Blum, A. 103 Blumenfeld, R. 481 Blumstein, J. 241 Bobes, M. A. 354 Bobholz, J. A. 288 Boccardi, E. 391 Boeglin, J. 95, 97, 100 Boelmans, K. 356 Bogen, J. 169 Bogousslavsky, J. 312, 317, 381 Bohl, J. 420 Boies, S. J. 332 Bojanowski, M. 188 Boller, F. 94, 188, 307, 441, 442, 454, 459, 459 Bolte, M. C. 270 Bondi, M. W. 420, 441, 443 Boner, L. 267 Boniface, F. 483 Bonin, G. 25 Boone, K. 482 Bor, D. 337 Borenstein, J. 492 Borggreve, F. 497, 503 Borod, J. C. 96, 427 Botez, M. I. 254, 277, 308

517

Botez, T. 308 Bottini, A. 56 Bottini, G. 288, 292, 298, 308, 314, 315, 317, 318, 319, 320, 321, 388 Botvinick, M. M. 347 Boucher, V. 196 Bouffard, M. 38 Bouillaud, J.-B. 51, 75, 76 Bourgouin, P. 337 Bousser, M. G. 310 Bouton, G. 213 Bouvard, G. 317 Bowers, D. 272, 320, 321 Boxer, A. L. 481 Boyes, C. 453 Boyko, O. B. 419 Boyle, P. A. 492 Bozeat, S. 253, 473, 474, 475, 478, 479 Braak, E. 420 Braak, H. 420 Bracewell, R. J. 100 Bradley, C. J. 491 Bradley, K. M. 502 Brady, J. M. 26 Braisby, N. 232, 234, 239, 241 Brambati, S. M. 56, 64, 68, 127 Bramwell, B. 93 Brandt, J. 414, 420, 443 Brashear, H. R. 268, 269 Braun, A. 40 Braun, C. 366 Braver, T. S. 347, 419 Breedin, S. D. 241 Brenneis, C. 67 Bressi, S. 450, 451 Bressman, S. 309, 317, 319 Breuleux, A. 100 Brewer, J. B. 415, 422, 426, 428 Brierley, B. 422 Brissaud, E. 52 Broadbent, D. E. 331, 352, 358, 359, 363 Broca, P. 25, 51, 75, 76, 77, 80, 93, 94, 169 Broggi, G. 312 Broida, H. 148 Bronson, M. B. 337 Brooks, W. S. 418 Brookshire, R. H. 148, 155 Brouwers, E. Y. 296 Brown, A. S. 456 Brown, C. P. 130, 131 Brown, G. 449, 450 Brown, J. 176 Brown, P. 165, 166 Brown, R. A. 429 Brown, R. G. 451, 461 Brownell, H. H. 95, 97, 98, 100, 101, 103, 232, 243 Bruce, C. 35 Bruckert, R. 241 Brunia, C. H. 366

518

Author index

Brunner, R. J. 309 Brunswick, N. 125, 127 Brust, J. C. 277, 309, 317, 319 Brysbaert, M. 205, 215 Bub, B. 122 Bub, D. 454 Buccino, G. 164, 289, 290 Buchel, C. 66, 421 Buchtel, H. A. 268, 269, 275, 276 Buckley, P. B. 215 Buckner, R. L. 36, 60, 426, 427 Buckwalter, J. G. 450 Bucy, P. C. 164 Budde, M. 427 Buell, U. 310 Bulau, P. 141 Bullis, D. P. 315 Bunge, S. A. 337, 338 Burani, C. 122 Bürgel, U. 31 Burgess, A. P. 367 Burgess, C. 99 Burkart, M. 458 Burke, D. M. 453, 456 Burki, M. 164 Burns, A. 459 Burns, P. 499 Burstein, D. 128, 130 Burton, H. 34, 287, 288, 289 Burton, M. J. 41 Busch, N. A. 366 Buschke, H. 449, 458 Bush, G. 337, 338 Bushnell, M. C. 288, 289, 337, 364 Butfield, E. 147 Butler, J. 148 Butter, C. M. 41 Butters, M. A. 420 Butters, N. 414, 420, 441, 442, 443, 445 Butterworth, B. 125, 202, 203, 206, 207, 214, 219, 220, 242 Buttet, J. 186, 187, 273 Buxbaum, L. 257, 262 Buxton, R. B. 353, 354 Bylsma, F. W. 443 Byma, G. 271 Byng, S. 120 Cabeza, R. 425, 426, 427 Cadoret, G. 27, 31, 34, 36 Cahill, L. 422, 428 Cahn-Weiner, D. A. 492 Caine, D. 414 Calder, A. J. 421 Caldwell, C. B. 310, 312 Caligiuri, M. P. 148 Caltagirone, C. 242 Calvanio, R. 260 Cambier, J. 275, 309, 317 Campbell, D. C. 309

Campbell, J. I. D. 207 Campbell, J. S. 26 Canavan, A. G. 443, 450 Canli, T. 422, 428 Cantagallo, A. 42 Canter, G. J. 272, 273, 277 Cao, Y. 140 Capitani, E. 148, 154, 188, 307, 479 Caplan, D. 448, 454 Caplan, L. R. 320 Cappa, S. F. 53, 56, 63, 64, 66, 67, 68, 127, 141, 149, 292, 298, 308, 309, 310, 311, 313, 315, 317, 319, 320, 454 Cappelletti, M. 473 Capps, J. L. 445 Caradoc-Davies, T. 446 Caramazza, A. 124, 191, 206, 232, 238, 243, 479 Carballido-Gamio, J. 133 Cardebat, D. 98, 140, 141, 493 Cardenas, V. 481 Carey, S. 201, 202, 214 Carmichael, S. T. 41, 311, 382 Carpenter, K. 425 Carrier, B. 337 Carson, K. J. 503 Carstensen, L. L. 422 Carter, A. R. 128, 130, 131 Carter, C. S. 337, 340 Carusi, D. 492 Carvell, S. 455 Caselli, R. J. 294, 295, 297 Casey, B. J. 384 Casini, L. 365 Cassem, E. H. 338 Castaigne, P. 188, 317 Castiglioni, I. 67 Catani, M. 26, 310, 312, 313 Cate-Carter, T. D. 127, 132 Caton, R. 349 Cauthen, J. C. 308 Cavada, C. 32 Cave, K. R. 252 Caviness, V. S. 26, 32, 41, 318 Celani, M. G. 292, 315 Cermak, L. S. 420 Cestnick, L. 130, 131 Chain, F. 270, 275 Chaix, Y. 131 Champagne, M. 100, 103 Chan, D. 481 Chang Chui, H. 309, 317 Chanoine, V. 125, 127 Chantraine, Y. 103 Chapman, L. 140 Chapon, F. 317 Charcot, J.-M. 123 Charles, S. T. 422 Chase, C. 272 Chase, T. N. 461

Author index Chatterjee, A. 254, 257 Chawluk, J. 414 Chazot, G. 309, 317 Cheatwood, J. L. 313 Chedru, F. 270, 275 Chelazzi, L. 354, 356, 364, 365 Chemerinski, E. 491 Chen, L. 366 Chen, Q. 491 Chenevert, T. L. 216 Cherry, B. J. 450 Cherry, E. C. 352 Chertkow, H. 269, 454 Chiacchio, L. 450 Chiarello, C. 99 Chocholle, R. 270 Chochon, F. 215, 216 Cholewa, J. 122 Chow, T. 491, 502, 503 Chudasama, Y. 318 Chui, H. C. 253 Chun, M. M. 27, 361 Chung, C. S. 317, 318 Church, R. M. 214 Chusid, J. D. 25 Cicerone, K. D. 149, 388, 394 Cipolloni, P. B. 42 Cipolotti, L. 203, 206, 207, 208, 209, 211, 213, 219, 475 Clairet, S. 502 Claparède, E. 437 Clark, J. M. 207 Clark, M. G. 131 Clark, V. P. 350, 353 Clarke, R. J. 415, 426 Clarke, S. 149, 275, 276 Clarke, W. R. 309, 311, 312, 315, 317, 320 Clarkin, J. 343 Clegg, R. A. 420 Cloninger, C. L. 342 Coates, R. 53 Cocchini, G. 449 Code, C. 94, 95 Cogan, G. D. 307 Coghill, R. C. 288, 289 Cohen, J. D. 347, 384, 419 Cohen, L. 130, 203, 205, 209, 210, 211, 212, 215, 216, 220, 336 Cohen, N. J. 210, 213, 416, 420, 440, 442 Cohen, N. S. 190, 195 Cohen, R. 237, 492 Cohen-Mansfield, J. 492, 493 Cohn, T. 357 Colby, C. L. 364 Colcord, R. D. 195 Colebatch, J. G. 288 Colenda, C. C. 491 Coles, M. G. H. 337, 350, 362 Coletti, A. 174 Collette, F. 450, 503

519

Collins, M. 148, 153 Colombo, C. 124 Colombo, M. R. 321 Colson, C. 310 Coltheart, M. 120, 122, 124, 233, 308 Como, P. G. 451 Comper, M. 297 Connelly, A. 424, 425 Cook, P. R. 186 Cooper, J. M. 473 Cooper, L. A. 446, 447 Cooper, N. R. 367 Cooper, R. 201, 362, 365 Corbetta, M. 142, 252, 336 Corcoran, R. 388 Corina, D. 40 Corkin, S. 288, 294, 412, 413, 415, 418, 420, 422, 423, 424, 425, 426, 427, 428, 441, 442, 461, 481 Cornacchia, L. 308 Cornell, J. 497 Cornet, J. A. 204 Correa, A. 357 Corwin, J. V. 313 Cosgrove, G. R. 338 Coslett, B. 241 Coslett, H. B. 121, 255, 257, 258, 262, 268, 269, 272, 320, 321 Côté, H. 104 Cote, L. 450 Coull, J. C. 357, 364 Courchesne, E. 342 Couto, J. M. 127, 132 Cowan, W. M. 27 Cox, C. 461 Coyle, J. M. 168 Coyle, J. T. 311 Craig, A. 493 Craighero, L. 164 Craik, F. I. 388, 419, 448, 449 Crane, A. M. 382 Crerar, A. 269 Creutzfeld, O. 349 Crisi, G. 174 Cristescu, T. G. 358 Critchley, M. 94, 216, 308 Crivello, F. 216 Croft, R. J. 367 Crook, T. 493 Cross, K. 403 Cross, P. M. 188, 277 Crosson, B. A. 142, 178 Crowder, R. G. 189 Croxson, P. L. 26 Crucian, G. P. 168, 173 Crum, W. R. 481 Crutcher, M. D. 384 Cruttenden, A. 96 Cuddy, L. L. 188, 189 Cullen, K. 414, 418

520

Author index

Cummings, J. L. 273, 379, 393, 481, 482, 483, 491, 492, 493, 496, 499, 502, 503 Cunha, F. C. 171 Cunnington, R. 39 Curio, G. 289 Currie, J. 342 Curtis, L. E. 201 Dagenbach, D. 211, 212, 213 Dagos, J.-D. 317 Dahlberg, C. 149 Daigle, M. A. 104 Dairou, R. 309 Dale, A. M. 60, 351, 354, 415, 426 Dalla Barba, G. 456, 458, 459, 460, 462 Dal Martello, M. F. 218, 219 Dalrymple-Alford, J. C. 451 Dam, M. 311 Damasio, A. 19, 53, 253, 293, 296, 309, 317, 338, 380, 392, 395, 420, 421, 442 Damasio, H. 19, 53, 253, 309, 317, 338, 392, 397, 415, 420, 421 Dang, M. 188 Daniele, A. 454 Danna, M. 142, 143, 144 Dannenbaum, S. E. 450 D’Antona, R. 310 Dantzig, T. 219 Daoust, H. 103, 104 Darcourt, J. 138, 502 Daselaar, S. M. 427 Davachi, L. 426 David, R. M. 148, 150 Davidoff, J. 232, 233, 234, 235, 237, 238, 239, 240, 241, 242, 260 Davidson, B. J. 363 Davidson, J. 189 Davidson, P. S. 418 Davidson, R. J. 337 Davidson, W. 476, 477, 496, 498 Davies, P. 459 Davies, R. R. 484, 485 Davis, B. J. 25, 35 Davis, C. 413 Davis, D. L. 272 Davis, K. R. 76, 309 Davis, T. L. 57 Davis-Stober, C. P. 340 Dawson, D. 394, 400 Dax, M. 93 Deacon, T. W. 32 Debener, S. 351, 363 De Beni, R. 449 De Bleser, R. 113, 122, 123, 484 De Boissezon, S. 141 Decroix, J. P. 309, 317 De Deyn, P. P. 68, 93, 496, 497, 499, 502, 503 Deecke, L. 39 De Fanti, C. A. 56 DeFries, J. C. 127

Degaonkar, M. 310 De Gaspari, D. 56 Degos, J. D. 296, 317 De Gutis, J. 216 Dehaene, S. 130, 202, 203, 205, 207, 209, 210, 211, 212, 213, 214, 215, 216, 217, 220, 333, 336 Deiber, M. P. 288 Dejerine, J. 25, 27, 39, 52, 118, 119, 121 De Kovel, C. G. 127 De Lacy-Costello, A. L. 211 Delaloye, B. 317 Delaney, S. 446, 447 De la Sayette, V. 317 Delavelle, J. 215, 219 Delay, J. P. L. 297 Delazer, M. 204, 205, 206, 213 Delbeuck, X. 503 De Leon, M. J. 493 Dell’Acqua, R. 362 Della Sala, S. 170, 174, 210, 391, 449, 451 Delmas, A. M. 104 Deloche, G. 204, 206, 207 DeLong. M. R. 384 Delorme, A. 351 Delyfer, A. 104 De Marco, R. 56 Demery, J. A. 420 Demeurisse, G. 188, 196, 273, 277, 310 Demonet, J. F. 67, 125, 127, 130, 140, 141, 142, 493 De Mornay Davies, P. 473 Denckla, M. B. 205 Denenberg, V. H. 131 Denes, D. 213 Denes, F. 203, 213, 219 Denes, G. 206, 213, 237, 243, 270 Dennis, K. 204, 401 De Notaris, R. 5 De Olmos, J. 41 Deonna, T. 269 De Partz, M. P. 120 De Renzi, E. 141, 174, 175, 176, 178, 179, 231, 238, 243, 297, 307, 448 De Ribaupierre, F. 275 Derlon, J. M. 138 Dérouesné, J. 123 Deruaz, J.-P. 317 De Saint Martin, A. 269 De Saussure, F. 479 Desautels, M. C. 100, 103 Desban, M. 311 Desimone, R. 35, 252, 364, 365, 366 Desmond, J. E. 36, 415, 426 D’Esposito, M. 60, 67, 415, 418, 420, 426, 427 Deuchert, M. 289 Deutsch, D. 358, 359 Deutsch, G. 188 Deutsch, J. A. 358, 359 De Volder, A. 216, 220

Author index De Vos, R. A. 420 Deweer, B. 441, 442, 459 DeYoe, E. A. 355 Dickson, D. 189, 481, 483 Dimitrov, M. 380, 392 Dimond, S. J. 296 Dinov, I. D. 491, 499, 503 Di Piero, V. 56 Di Pietro, M. 278 Di Russo, F. 354, 364 Disbrow, E. 289 Disterhoft, J. F. 419 Ditterich, A. 31, 37 Dobbins, I. G. 415 Dobkin, B. H. 273 Dobrowolsky, S. 308, 312, 320 Doherty, J. 359, 364 Dolan, R. J. 66, 273, 338 Dolcos, F. 426, 427 Dominey, S. J. 367 Donaldson, D. I. 426 Donchin, E. 350, 362 Dong, Y. 342 Dori, H. 449 Doricchi, F. 308, 310, 313 Doring, W. 275 Dorrego, F. 491, 502 Double, K. L. 418 Dow, L. 321 Dowling, W. J. 185 Downey-Lamb, M. M. 419 Downing, P. E. 355 Doyle, M. C. 361 Doyon, B. 98, 493 Drachman, D. 493 Drake, J. 473 Drevets, W. C. 337, 382, 385, 391 Drews, E. 99, 140 Drislane, F. W. 130 Driver, J. 273, 321, 341 Drobnjac, I. 26 Dronkers, N. F. 481, 482 Druks, J. 232, 233, 234, 238, 242, 243 Druzgal, T. J. 427 Drysdale, K. A. 360 Dubois, B. 42, 313, 386, 460, 498 Ducarne, B. 275 Duchen, L. W. 481 Ducouer, S. 138 Dudchenko, P. 425 Duffau, H. 313 Duhamel, J.-R. 241 Dummett, M. 241, 242 Duncan, G. H. 337 Duncan, G. W. 76 Duncan, J. 252, 337, 352, 359, 361, 364, 365 Du Plessis, D. 484 Dupont, P. 216 Dupoux, E. 215 Durand, M. 76

521

Durham, A. 38 Dusser de Barrene, J. G. 25 Early, T. S. 342 Ebbinghaus, H. 412 Ebert, P. L. 310, 312 Eck, K. 104 Eckholdt, H. M. 458 Edwards-Lee, T. 482 Efron, R. 255 Ehrlich, L. E. 310, 312 Eibl, G. 204 Eichenbaum, H. 413, 416, 424, 425 Eimer, M. 353, 356, 365 Eisenberg, H. M. 188 Eisenson, J. 94, 101 Elbert, T. 366 Elghozi, D. 309, 317 Elithorn, A. 357 Elliott, R. 96 Ellis, A. W. 124, 231, 269, 311, 475 Ellis, L. K. 338 Enderby, P. 148, 149, 150, 155 Endo, K. 293, 295, 296 Engel, A. K. 363, 366 Engel, D. 237 Engelborghs, S. 68, 93, 493, 496, 497, 498, 502, 503 Engelien, A. 275 Epstein, R. 262 Ergis, A. M. 441, 442 Eriksen, C. W. 252 Erzinclioglu, S. 402 Escourolle, R. 275 Eshel, Y. 211 Eslinger, P. J. 380, 381, 385, 388, 391, 392, 394, 395, 397, 401, 403, 441 Esso, K. 340 Eure, K. F. 77 Eustache, F. 267, 274, 275, 317 Evans, A. C. 36, 37, 39, 40, 288, 289, 384, 388, 407, 418 Evans, D. E. 343 Fabbro, F. 68 Fadiga, L. 164 Faglia, L. 93 Faglioni, P. 94, 173, 174, 175, 176, 231, 243, 274, 275 Fairbanks, L. 491, 492, 493, 499 Fallon, J. 35 Fama, R. 420 Fan, J. 336, 337, 338, 339, 340, 342 Fan, S. 350, 353, 366 Fanini, A. 356 Farah, M. J. 67, 252, 253, 256, 259, 260, 261, 262, 296, 297, 415, 426, 454 Fayol, M. 217, 220 Fazio, F. 56, 125, 127, 308, 309, 310, 315, 317, 320

522

Author index

Fecteau, S. 273 Fedio, P. 480 Feeney, D. M. 311, 313 Feigenson, L. 214 Feinberg, T. E. 82 Feldman, M. 250 Feldo, P. 461 Felleman, D. J. 355 Feng, Y. 127, 132 Ferber, S. 308, 311 Fernandez, B. 140 Fernandez-Duque, D. 342 Ferris, S. H. 492, 493 Ferro, J. M. 174, 309, 317, 320 ffytche, D. H. 310, 312, 313 Fias, W. 216, 221n4 Field, J. A. 455 Fierros, E. 20 Fiez, J. A. 35, 36, 68 Fincham, J. M. 242 Fincham, R. W. 269, 274, 275 Finger, S. 311 Fink, G. 138, 273, 321 Finkel, S. I. 499 Finkelburg, F. 170, 231 Finkelstein, S. 76 Finlay, D. C. 360 Fiorello, T. 491 Firth, C. 275 Fischer, R. 420 Fisher, S. E. 127, 132 Fitch, R. H. 128, 130, 131 Fitzpatrick, E. 320, 321 Fitzpatrick, P. 153 Fitzpatrick-DeSalme, E. 258 Flaherty-Craig, C. 397 Flamm, L. 102 Fleet, W. S. 172 Fleischman, D. A. 445 Fleurant, J. 196 Flitman, S. 215 Flombaum, J. I. 336 Fodor, J. 240, 242 Fogassi, L. 164 Foldi, N. S. 102 Folstein, M. 493 Folstein, S. E. 443, 493 Fonagy, P. 336 Fontaine, F. 188 Foote, S. L. 332 Ford, J. 190 Forde, E. M. E. 177 Forette, F. 188 Fornari, E. 275, 276 Forsman, A. 502, 503 Forssberg, H. 340 Forstl, H. 459 Forté, D. 104 Fortin, N. J. 416, 425 Fossati, P. 441, 442

Fossella, J. 339 Foundas, A. L. 77, 163, 166, 174 Fournet, N. 451 Fournier, J. P. 138 Fow, H. 498 Fox, J. H. 449 Fox, N. C. 481, 503 Fox, P. T. 36, 54, 288, 336 Foxe, J. J. 366, 367 Frackowiak, R. S. J. 35, 40, 140, 277, 288, 321, 481, 482, 483 Frak, V. 215, 220 Francks, C. 127, 132 Francois, C. 141, 187 Frank, L. R. 353, 354 Franke, B. 127 Franklin, S. 241, 243, 269 Franssen, E. 492 Frederiksen, C. H. 100 Freedman, M. 394, 400, 420 Freidman-Hill, S. 257 Freiwald, W. A. 367 French, J. D. 25 Freud, S. 52 Freund, C. S. 89 Freund, H. J. 164, 171, 173, 289, 290 Frey, S. 36, 42 Friberg, L. 335 Friden, T. 148 Fridman, A. 241 Friederici, A. D. 68 Friedland, S. 272 Friedländer, C. 267 Friedman, D. P. 286 Friedman, J. T. 131 Friedrich, F. J. 341, 343 Fries, P. 366 Frischknecht, R. 275 Friston, K. 66, 288, 351, 421 Frith, C. D. 3, 321, 338, 421 Frost, J. A. 288 Frost, S. J. 131 Frustaci, M. 124 Fu, S. 366 Fujii, T. 241, 275, 296, 297 Fujimori, M. 241, 296, 297 Fukatsu, R. 275 Fukuda, H. 273 Fuld, P. A. 459 Fulham, W. R. 360 Fundarò, C. 195 Fung, T. D. 454 Funkenstein, H. 39, 76 Funnell, E. 121, 472, 473, 474, 475, 478, 479, 481, 483 Furlan, M. 1 Fuson, K. C. 204, 220 Fuster, J. M. 384, 397, 414 Futer, D. S. 188

Author index Gabrieli, J. D. E. 36, 337, 338, 422, 426, 428, 440, 441, 442, 445, 461 Gade, A. 503 Gadian, D. G. 424, 425 Gaffan, D. 313, 425 Gagnon, L. 97, 98, 191, 196 Gaiefsky, M. 142 Gailloud, P. 310 Gainnotti, G. 237, 242, 454 Galaburda, A. 127, 128, 130, 131 Galambos, R. 366 Galante, E. 475 Galimberti, P. M. 307 Gall, F. J. 75, 76, 77, 310, 437 Gallen, C. 366 Gallese, V. 164 Gallistel, C. R. 202, 204, 217 Gallup, G. G., Jr. 402 Galton, C. J. 473, 480, 481, 483, 485 Galton, F. 18 Gandola, M. 308, 317 Garakian, J. 491, 502, 503 Garcia, L. J. 196 Garcia-Bunuel, L. 148, 155 Gardner, H. 19, 20, 97, 98, 101, 102, 237 Garol, H. W. 25 Garrard, P. 253, 478, 479 Garraux, G. 503 Garron, D. C. 451 Gazzaniga, M. S. 94, 169, 334 Geder, L. 391 Gedney, M. 42 Geehan, G. R. 267, 268, 275 Gehi, A. 288 Geiger-Kabisch, C. 459 Gelade, G. 252, 356 Gelb, A. 254 Geldmacher, D. 89, 502 Gelman, R. 202 Geminiani, G. 320 Généreux, S. 104 Gentileschi, V. 210 Gentner, D. 234, 235, 236, 237, 240, 241 George, K. P. 140 George, N. 273 Georgopoulos, A. P. 34, 333 Georgotas, A. 492 Gerardi-Caulton, G. 338 Geri, E. 148, 154 Gersh, F. 53, 296 Gertsmann, J. 215, 219 Gerundini, P. 56 Geschwind, N. 25, 26, 39, 52, 119, 127, 128, 131, 161, 162, 163, 168, 169, 170, 173, 175, 231, 310, 312 Ghaemi, M. 138, 188 Gholkar, A. 268, 274, 277 Ghose, G. M. 358, 364 Giacino, J. T. 394 Giannakopoulos, P. 42

523

Gibbons, Z. C. 473, 474 Gibbs, R. W., Jr. 102, 105 Gibson, J. J. 479 Gilad, R. 211 Gilardi, M. C. 67 Gilchrist, I. D. 321 Gilio, F. 165 Gilman, C. B. 204, 215, 217 Giordano, A. 451 Girault, J. A. 311 Girelli, L. 204, 205, 206, 213 Girling, D. M. 471 Giroux, F. 97, 98, 102, 103, 104 Giustolisi, L. 454 Givre, S. J. 354 Gjedde, A. 288, 289 Glascher, J. 421 Gleason, J. B. 154 Glisky, E. L. 418 Gloning, K. 148, 154 Glosser, G. 262, 426 Glover, G. H. 36 Glowinski, J. 311 Gobbini, E. I. 252, 262 Gobel, S. M. 217 Godersky, J. 169 Goekoop, R. 503 Goel, V. 402 Goeman, J. 496, 497, 503 Golby, A. J. 415, 426 Gold, B. 402 Goldacre, B. 67 Goldberg, E. 334 Goldberg, G. 173 Goldberg, M. E. 364 Goldblum, M.-C. 188, 454, 458, 459 Goldenberg, G. 419 Goldman-Rakic, P. S. 32, 38, 382, 384, 394, 418 Goldsher, D. 393, 402 Goldstein, K. 162, 163, 231, 233, 241, 242, 244, 254 Goldstein, M. H. 38 Goleman, D. 19, 21 Gomez, C.-M. 459 Gonyea, E. F. 168 Gonzalez, F. 351 Gonzalez, R. G. 413 Gonzalez-Rothi, L. J. 82, 84 Goodale, M. 251 Goodglass, H. 86, 154, 165, 168, 241, 453, 498 Goodman, R. 124, 206 Goodman-Shuman, R. A. 124, 206 Gopinath, K. S. 142 Gordon, B. 238, 310 Gordon, J. K. 196 Gordon, W. P. 194 Gornbein, J. 491, 492 Gorno-Tempini, M. L. 481, 482, 503 Gotham, A. M. 461

524

Author index

Gottlieb, D. I. 27 Goulding, P. J. 243, 472, 475, 481 Goulet, P. 95, 97, 98, 99, 100, 101, 102, 103, 104 Govoni, R. 449 Gow, C. A. 370 Grabowecky, M. 257 Grady, C. L. 342, 427 Graf, P. 444 Graff-Radford, N. R. 169, 414, 420 Grafman, J. 215, 379, 380, 386, 392, 397, 420 Grafton, S. T. 288 Graham, J. 267 Graham, K. S. 473, 475, 479, 481, 483 Graham, N. 473, 474 Graham, R. 426 Grant, L. 189 Grattan, L. M. 388, 391, 394, 395 Grave, D. P. 351 Graveleau, P. 309, 317 Gray, A. 499 Gray, C. 210 Gray, F. 296, 317 Gray, K. 492 Green, E. 154 Green, G. G. R. 38, 188, 268, 274, 276, 277 Green, J. D. 458 Greenberg, J. P. 254, 255 Greener, J. 149, 155 Greenwald, M. L. 179 Greenwood, R. 267 Gregory, C. 402, 473, 474 Griffin, I. C. 357, 358, 359, 364 Griffiths, H. 473 Griffiths, T. D. 38, 188, 267, 268, 274, 276, 277 Grigorenko, E. L. 127 Grill-Spector, K. 252, 262 Gross, C. G. 35, 26 Grossi, D. 307, 450 Grossman, M. 204, 243, 401, 403, 454, 455, 475, 476, 477, 481, 483 Grossman, R. I. 414 Growdon, J. H. 420, 422, 442, 461, 481 Gruber, D. B. 340 Gruber, T. 363, 366 Grutzner, G. 171 Gruzelier, J. H. 367 Guariglia, C. 315 Guieu, J. D. 275 Guilford, J. P. 17 Guillaume, S. 141, 187 Guimereas, A. R. 288 Guiz, J. 449 Gur, R. C. 414, 450 Gur, R. E. 450 Gurd, J. M. 37, 455 Gustafson, L. 476, 481, 483, 484, 496 Gutnick, M. J. 130 Haaland, K. Y. 165, 166, 171, 172, 173

Hackett, T. A. 27, 32, 35, 38 Hagen, C. 148, 154 Hagenlocker, K. 480 Hahn, V. 459 Hahn-Barma, V. 498 Halgren, E. 351, 424 Halgren, S. 290 Halliday, G. M. 414, 418, 484, 485 Halligan, P. W. 307, 314, 315, 317, 321 Halparin, J. D. 340 Halpern, A. R. 185 Halpern, C. 204 Halsband, U. 171 Haltia, T. 127 Hämäläinen, M. 349 Hamby, S. 102 Hamel, C. 103 Hammeke, T. A. 172, 288 Hampson, S. 366 Hampton, J. A. 241 Hamsher, K. 53 Hanlon, R. E. 420 Hanna-Pladdy, B. 163, 164, 174 Hannequin, D. 95, 97, 100 Hansch, E. C. 451 Hansen, J. C. 353, 356 Happé, F. 103 Harasty, J. A. 418 Hari, R. 349, 350 Harlock, W. 53 Harlow, J. M. 379 Harrington, D. L. 165, 166, 171, 172, 173 Hart, J. 238 Harter, M. R. 365 Hartikainen, K. M. 482, 483, 496 Hartley, A. 449 Hartman, J. 148 Harvey, M. 321 Harwood, D. 185 Hasegawa, M. 484 Hasegawa, T. 293, 296 Hasselbalch, S. G. 503 Hauck, R. 401 Hauser, L. B. 201 Hauser, M. 201, 214 Haws, B. 320, 321 Haxby, E. 67 Haxby, J. V. 252, 262, 342 Hay, D. 342 Hayakawa, Y. 296, 297 Hayward, R. W. 53 Haywood, C. S. 96 Hazlewood, R. 451 Head, H. 75, 79, 292, 294 Healey, E. C. 195 Healton, E. B. 309, 317, 319 Hebb, D. O. 332 Hébert, S. 188, 189, 191, 195, 196 Hécaen, H. 52, 96, 205, 215, 291, 308, 311 Heekeren, H. R. 63, 64, 66

Author index Heidler, J. 310 Heil, M. 362 Heilman, K. M. 75, 82, 84, 89, 163, 164, 165, 166, 168, 169, 170, 171, 172, 173, 174, 175, 176, 178, 179, 268, 269, 272, 308, 309, 311, 313, 317, 318, 319, 320, 321 Heindel, W. C. 440, 442, 443, 454, 455 Heinze, H. J. 353, 356 Heiss, W. 138, 148, 154, 188 Heister, J. G. 127 Heller, H. S. 453 Helm, N. A. 141, 187, 188 Helm-Estabrooks, N. 153 Helmholtz, H. L. F. 351 Henaff-Gonon, M. A. 241 Henderson, V. W. 450 Hendrickson, A. E. 27 Henin, D. 309 Hennighausen, E. 362 Henning, G. B. 277 Henriksen, L. 172 Henry, R. G. 131, 133 Henschen, S. E. 205, 215 Henson, R. N. A. 415 Herholz, K. 138 Herman, A. E. 128, 130, 131 Herrmann, C. S. 366, 367 Herrnstein, R. 17, 18, 19, 20 Hershey, K. 338 Herskovits, E. H. 310 Herzog, H. 337 Hess, C. W. 164 Hetherington, C. R. 370 Heun, R. 458 Heywood, C. A. 255 Hienz, R. D. 38 Hier, D. B. 309, 319, 480 Hikosaka, K. 35 Hillis, A. E. 238, 242, 310, 476, 477, 479 Hillyard, S. A. 350, 352, 353, 360, 361, 363, 364, 365 Himmelbach, M. 308, 311, 312 Hink, R. F. 352 Hino, H. 484 Hinrichs, J. V. 449, 458 Hirayama, K. 296 Hirono, N. 491, 499, 502, 503 Hirsch, E. 269 Hirsch, J. 57 Hitch, G. J. 417, 419, 447, 450 Hittmair-Delazer, M. 213, 214 Hjaltason, H. 320 Hockin, J. C. 420 Hodges, J. R. 67, 243, 253, 420, 451, 458, 472, 473, 474, 475, 478, 479, 480, 481, 482, 483, 484, 485, 497, 503 Hoesen, G. V. 414, 420 Hoffman, E. A. 252, 262 Hoffmann, H. 52 Hoffmann, J. E. 252

525

Hofman, P. A. M. 420 Hol, F. A. 127 Holcombe, A. O. 352 Holland, A. L. 148, 155 Holmes, A. P. 66 Holmes, G. 255, 294 Holroyd, C. B. 337 Homberg, V. 443 Hopf, J. M. 356 Horn, S. 450 Hornak, J. 42, 313, 392, 393 Horner, J. 254 Houchin, J. 349 Hough, M. S. 243 Houiller, S. 205, 215 Houle, S. 388, 402 Howard, D. 238, 240, 241, 242, 243, 269, 476, 479 Howard, L. A. 451 Howard, R. J. 26 Huber, W. 139, 140, 148, 275 Hublet, C. 188, 196, 273, 277, 310 Hübner, R. 363 Hudson, A. J. 483 Huettel, S. A. 351 Huff, F. J. 481 Hughlings Jackson, J. 52, 231, 249 Hulme, C. 449, 450 Hummelsheim, H. 164, 173 Humphreys, G. W. 36, 177, 252, 258, 259, 260, 261, 262, 299 Humphreys, P. 128 Hurtig, H. I. 450, 455 Husain, M. 321 Husserl, E. 437 Hutchinson, J. 237, 238 Hyakawa, Y. 241 Hyde, K. 277 Hyde, M. 154, 241 Hyman, B. T. 413 Hyvarinen, J. 34, 38, 287 Iavarone, A. 459 Ibanez, V. 356 Ibuchi, Y. 420 Iglesias, S. 267 Ikejiri, Y. 499, 502 Imaizumi, S. 273 Imamura, T. 499, 502 Imura, T. 475 Indefrey, P. 67 Ingvar, D. H. 288, 335 Inman, V. W. 448, 450 Inoue, A. 420 Inoue, N. 269, 275, 276 Insausti, A. 413 Inzitari, D. 421 Iseki, E. 484 Isensee, C. 139, 140, 310 Ishihara, K. 391

526

Author index

Ishii, K. 502 Ivanoiu, A. 209, 473, 474 Iversen, S. D. 35 Ivory, S. J. 446 Ivry, R. B. 252 Iwai, E. 35 Iwatsubo, T. 484 Jackson, M. 483 Jacobs, K. M. 128, 130 Jacobs, M. A. 310 Jacome, D. E. 186, 188 Jacques, T. Y. 338 Jacquier, M. 204 Jagella, C. 311 Jagust, W. 482, 483, 496 Jakobson, L. S. 188, 189 Jakubek, K. 419 Jaldow, E. 473 James, M. 204, 259 James, W. 54, 331, 416, 437 Jancke, L. 290 Janer, K. W. 336 Janowsky, J. S. 400, 414, 418 Jansen, E. N. 420 Janssen, P. 358, 364 Jasper, H. 286, 287, 289 Javet, R. C. 186, 187 Jellison, J. A. 189 Jenkins, W. 271 Jenner, A. R. 131 Jennings, J. M. 448 Jensen, A. 17 Jerger, J. 276 Jerger, S. 276 Jesmanowicz, A. 172 Jewesbury, E. C. O. 308 Jezzard, P. 40, 384 Jibiki, I. 475 Jibu, T. 361 Jin, Z. 127, 131 Joanette, Y. 93, 94, 95, 97, 98, 99, 100, 101, 102, 103, 104, 105, 273 Job, R. 362 Johansen-Berg, H. 26, 217 Johansson, B. 448 Johnson, A. F. 140 Johnson, J. 64, 480 Johnson, K. A. 413 Johnson, M. G. 153 Johnson, R. 362, 427 Johnston, P. S. 271 Johnston, P. W. 35 Jolicoeur, P. 362 Jonas, S. 39 Jones, A. C. 148, 150, 154, 155 Jones, D. K. 26 Jones, E. 154 Jones, R. D. 451 Jonides, J. 67, 216, 384, 449

Jorgensen, H. S. 138 Joseph, P. A. 140 Josse, G. 420 Joubert, S. 102 Julien, C. 484 Juncos, J. 461 Junge, S. 366 Jurik, J. 480 Kaas, J. H. 27, 32, 35, 38, 286, 287 Kahneman, D. 331, 352, 363 Kalbe, E. 210, 503 Kalders, A. S. 451 Kalmar, D. 149 Kaminen, M. 127 Kaminen-Ahola, M. 128 Kamo, T. 267 Kan, I. P. 415, 426 Kanai, A. 484 Kandel, E. R. 429 Kang, Y. 317, 318 Kanizsa, G. 251 Kanske, P. 332 Kanwisher, N. 262, 273, 355 Kaplan, E. 162, 163, 165, 168, 169, 175, 498 Kapur, N. 420, 421 Kapur, S. 388, 402 Karbe, H. 138, 140, 188 Karnath, H. O. 308, 310, 311, 312, 317 Kaszniak, A. W. 420, 441, 443, 449 Katsman, D. 311 Katsuragi, T. 484 Katz, J. J. 242 Katz, L. 131 Katz, M. 458 Katz, R. B. 86 Katzman, R. 459, 493 Kaufman, A. S. 340 Kaufman, N. L. 340 Kaufmann, L. 204 Kawamura, M. 296, 391 Kawashima, R. 273 Kay, J. 122, 124, 233 Kaye, J. A. 418 Kazui, S. 269, 275, 276 Keating, D. P. 201 Keil, A. 366 Keim, R. 68 Keith, R. L. 186 Kelter, S. 237 Kelly, M. P. 480 Kemeny, S. 140 Kempler, D. 195 Ken, L. 476 Kennard, C. 308, 311, 313, 321 Kennedy, D. N. 26, 32, 41, 318 Kensinger, E. A. 415, 422, 423, 425, 426, 428 Keplinger, J. E. 164 Kerl, J. 128 Kerns, K. A. 340

Author index Kertesz, A. 53, 137, 148, 174, 277, 308, 309, 312, 317, 320, 476, 477, 496, 498 Kessler, J. 138, 188, 210 Keyl, P. M. 443 Kiebel, S. 141 Kiefer, M. 362 Kilgour, A. R. 189 Kim, K. H. S 57 Kimura, D. 34 Kimura, I. 275 King, E. M. F. 502 King, F. A. 308 Kinsbourne, M. 220 Kintsch, W. 449 Kiritani, S. 273 Kirshner, H. S. 480 Klawans, D. 451 Klawans, H. L. 451 Kleffner, F. R. 269 Klein, D. 36 Kleinschmidt, A. 290 Kleist, K. 163, 174 Klingberg, T. 340 Knesevich, M. A. 342 Knibb, J. A. 480 Knight, R. G. 446 Knight, R. T. 165, 166, 171, 172, 173, 379, 415, 426 Knopman, D. 441, 443 Knott, R. 475 Knuttinen, M. G. 419 Kobayashi, S. 361, 365, 367 Kochanska, G. 338 Koechlin, E. 215 Koehler, P. J. 311 Koening, A. L. 338 Koeppe, R. A. 67, 384, 449 Koivisto, M. 98, 99, 446 Kok, A. 362 Kolb, B. 173 Kolinsky, R. 188, 196, 273, 277 Koller, W. C. 455 Kolodny, J. 337 Konishi, S. 426 Kopelman, M. D. 450, 473 Kornblum, H. I. 311 Kornhaber, M. 20 Kornhuber, H. H. 39, 309 Korsakoff, S. S. 437 Kosatsky, T. 420 Kosslyn, S. M. 338 Kostopoulos, P. 36, 42 Kouider, S. 67 Koulibaly, P. M. 502 Koutstaal, W. 415, 426 Krabbendam, L. 420 Kramer, A. F. 354 Kramer, J. H. 480, 482, 483, 496 Kramer-McCaffery, T. 321 Kranczioch, K. 363

527

Krasnegor, N. A. 394 Krause, T. 289 Kreiman, J. 273 Kreiter, A. K. 367 Kremer, J. 491 Kremser, C. 67 Krendl, A. C. 422, 423 Kril, J. J. 414, 418, 484, 485 Kritchevsky, M. 414 Kroll, J. F. 64 Krubitzer, L. 289 Kumagai, T. 420 Kunz, T. 309 Kuo, S. B. 491 Kurtzke, J. F. 148 Kuskowski, M. A. 451 Kuslansky, G. 458 Kussmaul, A. 79, 81, 82, 83, 84, 269 Kustov, A. 38 Kutas, M. 361 Kuypers, H. G. 164 Kuzis, G. 491, 502 Kwok, S. 403 Kwong, K. K. 57 Ky, K. N. 20 Laatu, S. 455 Laberge, D. 333 Labouvie-Vief, G. 440 Labrecque, R. 188, 196, 268, 273, 277 Lafaille, P. 273 Laganaro, M. 278 Laiacona, M. 174 Laine, M. 98 Lamassa, M. 292, 315, 421 Lambert, J. 141, 267, 270, 274, 275, 276, 277 Lambon Ralph, M. 253, 269, 475, 478, 479, 480, 481, 482, 483 Lamme, V. A. F. 354 Lammertyn, J. 216 Lamoureux, M. 103 Lampl, Y. 211 Landau, W. M. 148, 269 Landauer, T. K. 215 Landes, A. M. 502 Landis, T. 215, 219 Lang, A. E. 461 Langdon, D. W. 234 Lange, G. 427 Lange, H. W. 443 Lange, J. J. 356 Lange, K. L. 454, 455 Lange, K. W. 451 Langenbahn, D. M. 149 Lantos, P. L. 483 Lantz, G. 351 Laplane, D. 317 Larsen, B. 294 Larson, C. L. 337 Lasley, D. J. 357

528

Author index

Lassen, N. A. 172, 335 Laughlin, S. A. 194 Laurent, B. 309, 317 Lauritzen, M. 172 Làvadas, E. 320 Lavie, N. 363 Lavikainen, J. 366 Lawrence, A. D. 451 Lawrence, C. 357 Lawrence, D. G. 164 Lawson, D. 353 Lease, J. 418, 427 Lease-Spellmeyer, J. 254 Le Bihan, D. 130, 215, 216, 220 Le Blanc, B. 98 Lechevalier, B. 267, 274, 275 Lecky, B. 267 Le Clec’H, G. 130, 216, 220 Lecours, A. R. 93, 103 LeDoux, J. E. 334, 421 Lee, G. 449, 450 Lee, J. R. 131 Lee, K. H. 317, 318 Lee, K. M. 57 Lee, L. 491, 499 Lee, T. M. C. 342 Leeman, B. 278 Lees, A. J. 172, 450 Leibovitch, F. S. 310, 312 Leinonen, L. 34, 38 Leischner, A. 147 Legér, A. 142 Leiguarda, R. 172 Lemieux, S. 102, 419 Lendrem, W. 148, 150, 154, 155 Lenneberg, E. H. 64 Lennox, G. 483 Lenz, D. 366 Lenzi, G. L. 308, 309, 310, 315, 317, 320 Leonard, C. M. 35 Leonards, U. 356 Lepage, Y. 103 Lepsien, J. 359 Lercari, L. P. 340 Leroy-Willig, A. 288 Leschziner, G. 481 Lesk, D. 137 Lesser, R. 122, 124, 232, 448 Levander, M. 320 Levelt, W. J. M. 67 Leveroni, C. L. 273 Levesque, J. 337 Levin, H. M. 379, 388 Levin, H. S. 188 Levine, B. 394, 400, 424 Levine, D. 260 Levita, E. 137, 147, 154 Levitin, D. J. 186 Levy, K. 343 Levy, M. L. 493

Levy, R. 313, 459 Lewandowsky, M. 205, 210, 211 Ley, E. 357 Leys, D. 275 Lhermitte, F. 93, 241, 270, 275, 295 Lichtheim, L. 25, 80, 81, 82, 83, 84, 268, 269, 310, 312 Liepmann, H. 52, 162, 163, 164, 168, 169, 170, 177, 179 Light, L. L. 445, 453 Lin, C. S. 286 Lincoln, N. B. 148, 150, 154, 155 Lindemann, M. 213 Lindholm, J. M. 448 Linenweber, M. R. 140 Ling, P. K. 102 Linnankoski, I. 34 Lippmann, N. 17 Lipton, R. B. 458 Lissauer, H. 250, 251, 253, 260, 292 List, G. 237 Litvan, I. 461, 498 Livingstone, M. 127, 130 Lloyd, J. J. 496, 503 Locascio, J. J. 420 Lochy, A. 219 Logan, J. M. 427 Logie, R. 449, 451 Lomber, S. G. 313 London, E. D. 311 Longmore, B. E. 446 Longuet-Higgins, F. R. S. 218, 221n1, n5 Lorch, M. P. 149 Lorente de No, R. 349 Lorenzo, G. D. 451 Loring, D. W. 164 Louarn, F. 296, 317 Lough, S. 402 Low, A. A. 205, 206, 211 Lowe, J. 483 Lualdi, M. 321 Lucchelli, F. 176, 178, 179 Lucchese, D. 237, 243 Luck, S. J. 353, 356, 361, 363, 364, 365 Luders, H. 289 Ludlow, C. 420 Luevano, L. F. 77 Lupianez, J. 357 Luria, A., 52, 186, 188, 255, 257# Lurito, J. T. 333 Lutzenberger, W. 366 Luu, P. 337, 338 Luzzatti, C. 113, 124, 171, 307, 472, 473 Luzzi, S. 188 Lynk, H. A. 147 Lyon, G. R. 130, 394 Lyytinen, H. 127 Maas, L. C. 133 Maas, O. 168, 169

Author index Macar, F. 365 Macciardi, F. 127, 132 Mack, L. 165, 166, 176 Mackenzie, C. 148 Mackey, S. 27, 31, 34 MacKinnon, C. D. 165 MacLean, P. D. 25 Macoir, J. 191, 475 MacPhie, I. L. 127, 132 Maeder, P. P. 275, 276 Maertens, K. 493, 496, 497, 502, 503 Maess, B. 366 Magni, E. 56 Mahagne, M. H. 138, 493 Maher, L. M. 166, 174, 179 Mahurin, R. K. 497 Mai, N. 254 Maietti, A. 42 Maine de Biran 437 Mair, W. G. 414 Makeig, S. 351, 366 Maki, T. 391 Makishita, H. 293, 295 Makris, N. 26, 32, 41, 318 Malamut, B. 414, 440 Malcein, M. 422 Malec, J. F. 149, 388 Malenfant, D. 449, 450 Malhotra, P. 308, 311, 313 Mallard, A. R. III 195 Malloy, P. F. 492 Malmo, R. 308, 311 Malone, V. 342 Malt, B. C. 241 Mampaey, E. 498 Manchester, J. 453 Mancini, F. 195 Mandler, G. 444 Mandon, S. 367 Mangun, G. R. 353, 364, 365 Mann, D. M. 496 Mannan, S. K. 308, 311, 313 Manry, C. 270 Maquet, P. 269 Maravita, A. 317, 318, 319 Marcel, A. J. 333 Marchal, G. 138 Marcie, P. 96 Marcuse, H. 176 Marescau, B. 502, 503 Maresceaux, C. 269 Marie, N. 141 Marié, R. M. 141 Mariën, P. 67, 68, 93, 493, 496, 497, 498, 503 Maril, A. 415, 426 Marin, O. S. 188, 270, 334, 471, 472 Marinthe, C. 220 Mark, R. R. 457 Mark, V. W. 317 Markham, L. M. 451

529

Markman, E. 237, 238 Markowitsch, H. J. 273, 420, 424 Marks, M. 147 Marlowe, W. 388 Marr, D. 252 Marsden, C. D. 172, 174, 450, 451, 461 Marsh, G. G. 451 Marsh, L. 420 Marshall, J. C. 120, 273, 307, 308, 314, 315, 317, 321 Marshall, R. C. 148 Marshuetz, C. 216, 449 Martignoni, E. 195 Martin, A. 67, 480 Martin, L. 402 Martinez, A. 353, 354 Martinez-Trujillo, J. C. 356 Martone, M. 443 Martory, M. D. 215, 219 Maruff, P. 342 Marx, M. S. 492, 493 Masdeau, J. C. 39 Mash, D. 414 Massey, E. W. 254 Massey, J. T. 333 Masson, M. 309, 317 Massulo, C. 242 Masterman, D. M. 491, 492, 499, 502, 503 Masterson, J. 232 Masuhara, S. 186 Matallana, D. 204 Mateer, C. A. 388, 394 Mather, M. 422 Mathuranath, P. S. 497 Mattingley, J. B. 321, 341 Mattioli, F. 420, 459 Mauguière, F. 309, 317 Maunsell, J. H. 358, 364 Mavlov, L. 277 Mayberg, H. S. 335, 343 Mayer, A. R. 273 Mayer, E. 215, 219 Mayeux, R. 450 Mazaux, J. M. 140 Mazoyer, B. 216 Mazziotta, J. C. 288 Mazzocchi, F. 53, 138, 307, 308 Mazzoni, G. 400 Mazzoni, M. 148, 154 McArthur-Jackson, C. 342 McCabe, P. 137, 476, 477, 496 McCallum, W. C. 332, 350, 365 McCandliss, B. D. 336, 339, 340, 361 McCarthy, G. 349, 350, 351, 361 McCarthy, R. 472 McCarty, R. A. 299 McClelland, J. 253, 475, 480 McCloskey, M. 191, 206, 208, 210, 211, 212, 213, 218, 221n5 McCrory, E. 125, 127

530

Author index

McCulloch, W. S. 25 McDermott, J. 273 McDonagh, A. M. 484 McDonald, J. A. 41 McDonald, S. 103 McFarling, D. 84 McGlinchey-Berroth, R. 315, 420 McGrath, J. 392, 393 McGuirk, E. 148, 150, 155 McHugh, P. R. 493 McInerney, S. 26, 32 McIntosh, K. W. 195 McKay, D. G. 453, 456 McKeith, I. G. 499 McKhann, G. M. 481, 483, 493 McKinney, M. 311 McLean, J. P. 333 McLoughlin, P. 242 McMillan, C. 204 McNeil, J. 211 McNeil, M. 100 Mead, L. A. 273 Meador, K. J. 164 Meadows, J. C. 253 Meck, W. H. 214 Medea, E. 321n1 Medford, N. 422 Medina, J. 240 Mega, M. 491, 492, 499, 502, 503 Mehler, J. 215, 220 Mehta, A. D. 354 Meikle, M. 148 Meininger, V. 241, 295 Melice-Ledent, S. 237 Mellet, E. 216 Mellits, D. 130 Mencl, W. E. 131 Mendez, M. F. 267, 268, 275 Mendoza, J. E. 163 Merello, M. 172 Merzenich, M. 271, 286 Messa, C. 56, 308, 309, 310, 317, 320 Messerli, P. 237 Mesulam, M. M. 42, 287, 313, 315, 359, 382, 414, 471, 472, 476, 477, 480 Metcalfe, J. 400 Metz-Lutz, N. M. 269 Meuli, R. A. 275, 276 Meurer, K. 422 Mevorach, C. 340 Meyer, E. 36, 288, 289, 384, 388, 407, 418 Meyer, J. W. 318 Meyer, R. 289 Meynert, T. 77, 79 Miceli, G. 242 Michel, C. 351, 356 Michel, F. 241, 267 Michelow, D. 98, 101 Mickel, S. F. 441 Migneco, O. 138

Mijovi, D. 320 Miklossy, J. 317 Milberg, W. P. 315, 453 Miller, A. 449 Miller, B. 379, 481, 482, 483, 493, 503 Miller, E. K. 364, 365, 418, 450 Miller, G. A. 354 Miller, N. L. 189 Miller, S. L. 271 Miller, S. P. 133 Milliken, B. 357 Mills, C. 341 Mills, D. 341 Milner, A. 251, 255, 308, 309 Milner, B. 36, 40, 42, 52, 173, 294, 298, 413, 414, 419, 437 Mine, S. 34 Miniussi, C. 353, 356, 357, 363, 364, 365 Minoshima, S. 384 Mintun, M. 36, 336, 384 Miozzo, A. 140, 420, 459 Mirzazade, S. 290 Mishkin, M. 42, 251, 424, 425, 440, 491, 499, 503 Mitchell, D. B. 456 Mitchell, J. P. 426 Mitchell, J. R. A. 148, 150, 154, 155 Mitchell, R. L. 96 Miyasaka, M. 293, 285 Mohlberg, H. 31 Mohr, E. 461 Mohr, J. P. 53, 76, 309 Moll, J. 171, 401 Mondlock, J. 320 Monetta, L. 100 Monoi, H. 475 Montanes, P. 204, 454 Montgomery, E. B. 455 Moody, S. 122 Moore, A. B. 142 Moore, A. P. 451 Moore, B. D. 188 Moore, C. I. 288 Moore, C. J. 36, 40 Moore, P. 204, 401, 403 Moran, J. 252, 364 Moreaud, O. 451 Morecraft, R. J. 42 Moretti, P. 148, 154 Morgan-Fisher, A. 272 Mori, E. 267, 268, 269, 270, 271, 274, 275, 276, 499, 520 Mori, K. 273 Mori, S. 26 Morris, J. 269, 338, 421, 427 Morris, R. 42, 450 Morrison, J. H. 332 Mort, D. J. 308, 311, 313 Mortimer, J. A. 451 Morton, J. 310

Author index Moscovitch, M. 388, 414, 424, 473 Moser, E. 39 Moss, H. E. 473 Mosso, A. 54 Motomura, N. 268, 270, 274, 275, 276 Motter, B. C. 356 Motto, C. 391 Mountcastle, V. B. 286, 334 Moyer, R. S. 215 Moyer, S. B. 122 Mozaz, M. 168 Mufson, E. J. 287, 382 Mukherjee, P. 131, 133 Mulder, G. 356 Mulder, L. J. 356 Mulhall, D. 148 Muller, M. M. 363, 366 Muller, S. P. 139, 140, 141 Mulley, G. P. 148, 150, 154, 155 Mummery, C. J. 67, 481, 482, 483 Munk, H. 52, 249, 250 Munoz, D. 476, 477, 496 Munte, T. F. 353, 356, 360 Murata, A. 34 Murayama, S. 391 Murman, D. L. 491 Murphy, D. R. 456 Murphy, K. 310 Murphy, P. J. 321 Murray, C. 17, 18, 19, 20 Murray, E. A. 286, 425 Murray, K. 338 Murray, M. M. 351 Musso, M. 67, 141 Myers, P. S. 95 Myllyluoma, B. 127 Na, D. L. 317, 318, 320, 321 Naatanen, R. 366 Naccache, L. 215, 216, 220 Nadeau, S. E. 90, 174 Nadel, L. 424 Nadkarni, N. 498 Naegele, B. 451 Naeser, M. A. 53, 194, 268, 269, 270, 271, 275 Nagarajan, S. S. 271 Nagele, T. 308, 310 Nagels, G. 493 Nagy, A. 502 Nakamura, J. 293, 296 Nakayama, H. 138 Nappi, G. 195 Nardocci, N. 312 Naritomi, H. 269, 275, 276 Nauta, W. J. H. 27, 382 Navarro, C. 309, 317, 319 Naveh-Benjamin, M. 449 Neary, D. 243, 472, 473, 474, 475, 476, 481, 483, 484, 496, 503 Nedjam, Z. 459, 460

531

Neisser, U. 352 Nelson, R. J. 286 Nelson, T. O. 400 Nespoulous, J.-L. 101 Nestor, P. J. 473, 483, 497, 503 Neuner, F. 273 Neville, H. J. 353 Newcombe, F. 120, 261, 271, 275 Newhart, M. 310 Newport, E. 64 Newsome, W. 25 Nicholas, M. 453 Nico, D. 315, 320 Nielsen, J. M. 85, 317 Nierenberg, A. A. 338 Nilsson, L. G. 457 Nirkko, A. C. 164 Nishino, H. 391 Nissen, M. J. 441, 443 Nobre, A. C. 352, 353, 356, 357, 358, 359, 361, 364, 365, 368 Nocentini, U. 99, 100 Noël, M. P. 206, 207, 208, 209 Noel, R. W. 116 Noll, D. C. 384 Nopola-Hemmi, J. 127 Noppeney, U. 231 Norman, D. A. 447, 448 Noth, J. 171 Nybäck, H. 210 Nyberg, L. 425, 426, 427, 446, 457 Nye, C. 149 Nyman, G. 34 Obler, B. A. 453 Obler, L. K. 96, 453 Ochipa, C. 178, 179 Ochsner, K. N. 337, 338 O’Connor, M. 420 O’Connor, S. M. 491, 492, 499 O’Craven, K. M. 57, 355 Odawara, T. 484 Odell, K. 100 O’Donovan, D. G. 483 Ogar, J. M. 481, 482 Ogarrio, C. 312 Oh, S. 476 Ohnuma, A. 275 Ohtake, H. 241, 296, 297 O’Kane, G. 425 Okita, T. 356, 361 Okubo, M. 186 Okuda, J. 269, 275, 276 Oldendorf, W. H. 308 Oliveira-Souza, R. 171, 401 Oliver, M. 308 Olofsson, U. 457 Olsen, T. S. 138 Olvera, A. 312 Ombredane, A. 76

532

Author index

Onton, J. 351 Opitz, B. 68 Oppenheimer, D. R. 275 Orban, G. A. 216 Orchard-Lisle, V. M. 242 O’Reilly, J. 357 Orlando, G. 174 Orsini, A. 450 Ortler, M. 67 Ostergaard, A. L. 242 Ostwald, P. F. 185 O’Sullivan, V. T. 502 Osumi, Y. 186 Otten, L. J. 361 Ottoboni, G. 171 Ousset, P. J 493 Owen, A. M. 418 Oxbury, J. 241, 309, 425 Oxbury, S. 241, 309, 414, 425, 472, 473, 474, 475, 478, 483 Ozdoba, C. 164 Paap, K. R. 116 Pacchetti, C. 195 Padmanabhan, S. 40 Padovani, A. 454 Paghera, B. 93 Palix, J. 356 Paljarvi, L. 414 Palladino, P. 449 Paller, K. A. 426 Palmer, A. R. 35 Palomba, D. 41, 362 Pambakian, A. 308, 311, 313 Pandya, D. N. 25, 26, 27, 28, 31, 32, 34, 35, 40, 41, 42, 318, 382, 384 Pantano, P. 310 Pantev, C. 366 Pantoni, L. 421 Paolo, A. M. 455 Papadimitriou, G. M. 41 Papagno, C. 56, 170, 174, 308, 317, 479 Papanicolaou, A. C. 188 Paracchini, S. 127, 132 Paradis, J. 196 Paramasivan, M. 128 Pardo, J. V. 288, 336, 342 Pardo, P. J. 336, 342 Pare, E. 254 Pariser, P. 317 Parkinson, S. R. 448, 450 Parlato, V. 459 Pascual-Leone, A. 303 Pasquier, F. 275 Passant, U. 476, 481, 483, 484, 496 Passingham, R. E. 41, 288, 450 Passman, L. J. 171 Patel, A. D. 268, 277 Patterson, K. 67, 120, 122, 123, 238, 240, 241,

243, 269, 308, 420, 472, 473, 474, 475, 476, 478, 479, 480, 481, 482, 483, 484, 485 Paulesu, E. 35, 56, 64, 67, 125, 127, 288, 308, 310, 314, 388 Paulsen, J. S. 456 Pavese, A. 257 Pavlov, I. V. 250 Pavlova, M. 366 Pawlik, G. 138 Payer, M. 104 Payne, B. 303 Payne, M. 443 Peach, R. K. 270 Pearlman, A. L. 253 Pebenito, R. 220 Peck, K. K. 142 Peden, J. K. 25 Pedersen, P. M. 138 Pegna, A. J. 215, 219 Peiffer, A. M. 131 Pellat, J. 451 Penfield, W. 38, 40, 172, 286, 287, 288, 289, 308, 311 Perani, D. 56, 63, 64, 66, 140, 142, 143, 144, 308, 309, 310, 311, 312, 315, 317, 320 Peretz, I. 97, 188, 189, 192, 196, 268, 269, 273, 277, 449, 450 Perfetti, C. A. 127, 131 Perl, T. M. 420 Pernet, C. 67 Peronnet, F. 267 Perrett, D. I. 338 Perry, D. W. 188 Perry, R. J. 458, 480 Pesciarelli, F. 362 Pesenti, M. 211, 212, 213, 216, 220 Pessin, M. S. 76 Petersen, S. E. 36, 68, 140, 142, 336 Petit, H. 275 Petracca, G. 491 Petrides, M. 25, 26, 27, 28, 31, 32, 34, 35, 36, 37, 39, 40, 42, 333, 384, 388, 407, 414, 418, 419, 427 Pezzini, A. 454 Pezzoli, G. 56 Pfaff, D. M. 339 Phengrasamy, B. 481, 482 Phillips, C. 351 Phipps, M. 380, 392 Pia, L. 308 Piaget, J. 337 Piatt, A. L. 455 Piazza, M. 202, 203 Piccirilli, M. 188 Pick, A. 176, 309, 471 Pickering-Brown, S. M. 484 Pickersgill, M. J. 148, 154 Pickut, B. A. 497, 503 Picton, T. W. 352 Pierce, K. 342

Author index Piercy, M. 271 Piguet, O. 422, 423 Pijnenburg, Y. A. 503 Pike, B. 26, 273 Pike, G. B. 36 Pillon, A. 219 Pillon, B. 42, 275, 441, 442, 460, 498 Pillon, J. 386 Pilon, M. A. 195 Pinard, M. 269 Pincus, D. 103 Pinel, P. 215, 220 Pinilla, T. 354 Pinker, S. 252 Pinsk, M. A. 26 Pirozzolo, J. 451 Pitres, A. 52, 123 Pizzamiglio, L. 315 Platel, H. 277 Platz, T. 293, 295 Playfer, J. R. 451 Poeck, K. 148, 472, 473, 484 Poggio, G. F. 286 Poirier, J. 296, 317 Poizner, H. 165, 166, 176 Poldrack, R. A. 36, 415, 426 Poline, J. B. 130 Polk, M. 277 Polkey, C. E. 450 Polster, M. R. 269 Poncet, M. 188, 241 Porrino, L. J. 382 Portin, R. 446, 455 Posner, J. 334 Posner, M. I. 36, 252, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 352, 363, 365 Postle, B. R. 418, 427 Potter, H. H. 97, 98 Potter, M. C. 361 Potzl, O. 254 Powell, M. C. 491 Power, J. M. 419 Power, R. J. D. 218, 219, 221n1, n5 Powis, J. 473 Pramstaller, P. P. 174 Pratt, K. H. 473 Pratt, M. W. 453 Preissl, H. 366 Press, D. M. 128 Press, G. 414 Pressing, J. 188 Preston, A. R. 419 Preuss, T. M. 27 Pribram, K. H. 25 Price, B. H. 338 Price, C. 36, 40, 66, 67, 140, 277, 481, 482, 483 Price, D. 337, 493 Price, J. L. 27, 41, 382, 385, 391 Prince, D. A. 128, 130

533

Prince, K. 422 Prince, S. M. 427 Prins, R. S. 154 Prinster, A. 40 Prinzmetal, W. 252 Prull, M. W. 36 Puel, M. 98, 142, 493 Pugh, K. R. 131 Pulvermuller, F. 366 Putnam, K. M. 337 Pylyshyn, Z. W. 352 Quadfasel, F. 162, 163 Quartarone, A. 165 Quatember, R. 148, 154 Quinlan, P. T. 299 Quinn, N. 450, 451 Raaschou, H. O. 138 Rabinowitz, J. C. 448 Racette, A. 189, 191, 192, 196 Radeau, M. 189 Rafal, R. D. 341, 343 Raichle, M. E. 36, 54, 68, 288, 335, 336, 337, 342, 351 Raife, E. A. 35, 36 Rainer, G. 418 Rainville, P. 337 Rakowicz, W. 497 Ralph, M. A. 473, 474, 475 Ramsberger, G. 153 Rancurel, G. 42 Randolph, C. 446 Rankin, K. P. 480, 481, 482 Rao, A. 353, 359, 364 Rao, S. C. 418 Rao, S. M. 172, 273, 288 Rapcsak, S. Z. 420 Rapp, B. C. 479 Rasmussen, T. 40, 287, 288, 294 Ratcliff, G. 261 Rattermann, M. J. 234, 235, 236 Rauschecker, J. P. 38 Rauscher, F. 20 Raven, J. C. 151 Rawson, M. D. 451 Raymer, A. L. 173 Raymer, A. M. 166, 178 Raymond, J. E. 361, 364 Raynaud, L. 220 Raz, M. 339 Raz, N. 457 Rebok, G. W. 443 Rebora, S. 307 Redlich, E. 254 Redmond. S. M. 164 Reed, B. R. 482, 483, 496 Reed, C. L. 290, 297 Reep, R. L. 313 Rees, A. 188, 268, 274, 276, 277

534

Author index

Rees, G. 276 Regan, D. 350 Regli, F. 312, 317 Regli, L. 276 Reich, T. 385 Reiche, W. 310 Reiman, E. M. 342 Reinikainen, K. 366 Reisberg, B. 492, 493 Reith, W. 140 Relkin, N. R. 57 Reminfer, S. 445 Remington, R. 333 Remis, R. S. 420 Remy, P. 141, 187, 288 Renaud, A. 100 Renowden, S. 425 Repp, B. 189 Reser, D. 38 Reuter-Lorenz, P. A. 449 Revesz, T. 483 Revonsuo, A. 455 Reynolds, J. H. 354, 364, 366 Reynvoet, B. 216 Rezak, M. 35 Ribot, T. 421, 437 Ricci, R. 321 Ricci, S. 292, 315 Rice, H. J. 415 Richardson, A. 127, 132, 484 Richardson, E. P. J. 309 Richman, J. M. 128 Rickard, T. C. 215 Riddoch, M. J. 252, 258, 259, 260, 261, 262, 299 Rieu, D. 462 Righetti, E. 292, 315 Rijntjes, M. 139, 140, 141 Rinaldi, J. F. M. 445 Ringelstein, E. B. 310 Ringman, J. M. 309, 311, 312, 315, 317, 320 Rinne, J. O. 414, 446 Rinne, U. K. 414, 455 Ritter, W. 350 Rivaton, F. 317 Rivière, D. 215 Rizzo, M. 53 Rizzo, V. 165 Rizzolatti, G. 164, 289, 290 Robb, W. G. K. 415 Robbins, T. W. 317, 451 Roberson, D. 232, 233, 234, 235, 237, 238, 239, 240, 241 Robert, P. H. 491, 502 Roberts, L. 38, 40 Roberts, P. M. 99, 100 Roberts, R. 414 Roberts, T. 289 Roberston, C. 451 Robertson, I. H. 341

Robertson, L. 257 Robey, R. R. 148, 149, 155 Robins, S. 453 Robinson, C. J. 34, 287 Robinson, D. L. 334, 364 Robson, M. D. 26 Rodier, P. M. 342 Rodriguez, V. 354 Roelfsema, P. R. 354 Roeltgen, D. P. 174 Rogers, T. 253, 474 Rohrer, D. 456 Roland, E. 294 Roland, P. E. 288, 291, 335 Rolke, B. 362 Rolls, E. T. 35, 42, 385, 392, 393, 401 Romani, C. 479 Romanski, L. M. 32, 38 Rombouts, S. A. 503 Romero, S. G. 215 Rorden, C. 308, 311, 312, 313, 321, 341 Rorie, E. E. 366 Rorie, K. D. 96 Rosa, M. 140 Rose, S. B. 269 Rosen, B. R. 288, 418, 426, 427 Rosen, G. D. 127, 128, 130, 131 Rosen, H. J. 140, 480, 481, 482, 483, 503 Rosen, T. J. 420, 441 Rosenberg-Thompson, S. 492 Rosene, D. L. 42 Rosenthal, A. S. 492, 493 Ross, E. 97, 272 Rossa, Y. 267, 275 Rossi, B. 149 Rossor, M. N. 483, 503 Rothbart, M. K. 337, 338, 340, 343 Rothi, L. J. G. 165, 166, 168, 170, 171, 172, 173, 176, 178, 179 Rothwell, J. C. 165 Rotte, M. 415, 426 Rottman, A. 84 Rottoli, M. R. 93 Roulet, E. 269 Roulin, J. L. 451 Rourke, B. P. 220 Rousseau, I. 188 Rowe, D. 276 Royall, D. R. 497 Rozzini, L. 454 Rubens, A. B. 39, 85, 250, 260 Rubin, J. 289 Rubin, N. P. 476 Rubin, S. R. 418 Ruch, T. C. 41 Rudge, P. 213, 293 Rueda, M. R. 340 Ruff, S. 142 Ruffino, M. 127 Rugg, M. D. 350, 351, 361, 415, 447, 457

Author index Rumbaugh, D. M. 339 Rumiati, R. I. 171 Rusconi, M. L. 292, 315, 317, 318, 319, 320 Rushmore, J. 313 Rushworth, M. F. 26, 217 Rusk, H. A. 147 Russell, C. 273 Russell, G. L. 482 Ruz, M. 361 Ryan, L. 424 Rymar, V. V. 26 Rypma, B. 427 Sabe, L. 491, 502 Sabourin, L. 98 Saccamanno, L. 340 Sadikot, A. F. 26 Saerens, J. 496, 497, 498, 503 Saetti, M. C. 297 Saffran, E. M. 121, 241, 253, 255, 257, 258, 270, 471, 472 Sagar, H. J. 461 Sahakian, B. J. 451 Sailer, U. 214 Saillant, B. 238, 241, 295 Saint-Cyr, J. A. 455, 461 Saito, H. A. 35 Salat, D. H. 418 Salazar, A. M. 392, 420 Salloway, S. 492 Salmelin, R. 350 Salmon, D. P. 440, 442, 443, 445, 450, 454, 455, 456 Salmon, E. 450, 503 Salob, S. P. 492 Salthouse, T. A. 448 Samson, Y. 42, 288, 310 Samsonovich, A. 424 Sanders, A. L. 427 Sandkuijl, L. A. 127 Sands, E. 147, 154 Sanides, F. 35 Sarazin, M. 42, 491, 498 Sarno, M. T. 137, 147, 154 Sarova-Pinhas, I. 211 Sartre, J. P. 437 Sasanuma, S. 475 Sattel, A. 459 Savaki, H. E. 311 Saver, J. L. 309, 311, 312, 315, 317, 320 Savoy, R. L. 57 Sawada, T. 269, 275, 276 Sax, D. 274, 275, 443 Sayjin, A. J. 450 Scahill, R. I. 481, 503 Scalaidhe, S. P. 418 Scammell, R. E. 296 Scarpa, M. 174, 388 Scerri, T. S. 127, 132

535

Schacter, D. L. 415, 426, 438, 439, 444, 445, 446, 447 Schaie, K. W. 440 Schall, J. D. 364 Schauer, G. F. 503 Scheffers, M. K. 356 Scheltens, P. 503 Schenone, P. 388 Schleicher, A. 31, 37 Schmahmann, J. D. 25, 312 Schmitt, F. A. 422 Schmitt, J. 171 Schmitt, M. A. 39 Schneck, M. 270 Schnider, A. 274, 276, 278 Schnider-Klaus, A. 274, 276 Schoene, W. C. 39 Schoenfeld, M. A. 356 Scholes, R. 272 Schoonen, R. 154 Schott, B. 309, 317 Schreiner, C. 271 Schroeder, C. E. 354 Schroth, G. 164 Schuff, N. 481 Schupp, C. 267 Schuri, U. 420 Schwab, A. 273 Schwartz, A. B. 333 Schwartz, M. F. 253, 471, 472 Schwartz, R. L. 173, 178, 320, 321 Schwarz, J. P. 3 Schwarz, M. 484 Schweinberger, S. R. 273 Schwent, V. L. 352 Schwiemann, J. 289 Sciarma, T. 188 Scifo, P. 56, 64, 67 Scotti, G. 231, 243 Scoville, W. B. 413, 437 Searle, J. R. 101 Sebestyen, G. N. 356 Seidenberg, M. 273, 475 Seiffert, A. E. 354 Seitz, R. J. 289, 290, 337 Seltzer, B. 35, 40, 42 Semenza, C. 213, 237, 243, 270 Semmes, J. 297 Senanarong, V. 491, 492, 499 Serafine, M. L. 189 Serdaru, M. 310 Sereno, M. I. 353, 354 Sergent, A. 97 Seron, X. 204, 206, 207, 208, 209, 211, 212, 213, 216, 217, 219, 220 Servo, A. 400 Sevush, S. 174 Sha, S. J. 480 Shadlen, M. N. 358, 364 Shah, N. J. 273, 290

536

Author index

Shakir, R. A. 188, 277 Shallice, T. 19, 123, 171, 231, 232, 233, 234, 238, 239, 241, 242, 243, 258, 447, 448 Shamay-Tsoori, S. G. 393, 402 Shamoian, C. A. 492, 493 Shanks, M. F. 473 Shankweiler, D. 147 Shapiro, K. L. 361, 362, 364 Shapiro, M. 425 Shavlev, L. 340 Shaw, C. L. 484 Shaw, G. L. 20 Shaw, P. 414 Shelepin, Y. 34 Shenkin, H. A. 41 Sherman, G. F. 127, 128, 131 Sherry, D. F. 438, 439 Shewan, C. M. 148 Shi, J. 484 Shimamura, A. P. 400, 414, 418, 445 Shimizu, N. 252 Shimomura, T. 499, 502 Shindler, A. G. 480 Shoham, S. 290 Shulman, G. L. 333, 336 Shults, C. W. 441 Shuren, J. 89, 174 Si, K. 429 Siddiqi, K. 26 Siebner, H. R. 165 Siegel, M. 243 Siegenthaler, A. L. 427 Signoret, J. L. 188 Silbersweig, D. 275 Silva, A. J. 429 Silveri, M. C. 242, 454 Silverman, J. 102 Silverman, M. 154 Simon, T. J. 214, 220 Simons, J. S. 473 Simpson, G. 99, 366, 367 Simpson, J. R. 385, 391 Simpson, T. L. 97, 98 Singer, H. D. 205, 206, 211 Singer, W. 266 Singh, A. 445 Sinkkonen, J. 366 Siok, W. T. 127, 131 Sirigu, A. 241, 386 Sjodin, A.-K. 502, 503 Ska, B. 101, 102, 103, 104 Skinhoj, E. 335 Slachevsky, A. 498 Slackmuylder, J. L. 310 Sliwinski, M. J. 458 Sloman, S. A. 237, 241 Smania, N. 308 Smith, A. D. 502 Smith, C. D. 422, 450 Smith, E. E. 67, 216, 384, 449, 450

Smith, M. L. 414 Smith, S. 445 Snowden, J. 243, 472, 473, 474, 475, 476, 481, 483, 484, 496, 503 Snyder, A. Z. 140, 142, 427 Snyder, C. R. 363 Snyder, D. R. 41 Soderstrom, H. 502, 503 Sokol, S. M. 206, 210, 211 Sokoloff, L. 54 Sokolov, A. 366 Somers, D. C. 354 Somers, N. 493 Sommer, T. 339 Song, A. W. 351 Soper, N. D. W. 502 Sorensen, A. G. 26, 32 Sorg, S. 41 Sorgato, P. 175, 176 Souza-Lima, F. 171 Sovijarvi, A. R. A. 38 Sparks, R. W. 141, 187, 188, 274, 275 Spatt, J. 479 Specht, K. 140 Speechley, M. 155 Speedie, L. 272 Spekreijse, E. H. 354 Spelke, E. 213 Spencer, D. 415, 426 Spencer, W. D. 457 Sperry, R. W. 94, 169 Sperry, S. D. 502 Spinelli, D. 364 Spinelli, L. 351 Spinnler, H. 94, 171, 210, 231, 238, 243, 274, 275, 276, 307, 391, 449, 451 Spreen, O. 269, 274, 275 Sprengelmeyer, R. 443 Spurzheim, J. K. 310 Squier, W. 425 Squire, L. R. 42, 400, 414, 416, 418, 420, 424, 425, 439, 440, 442, 444, 445 Stadelman, E. 205, 210, 211 Stadie, N. 122 Stadlan, E. M. 493 Stanescu-Cosson, R. 216 Stanger, B. Z. 441 Stanton, G. B. 364 Stark, R. E. 130 Starkey, P. 201 Starkstein, S. 172, 491, 502 Steck, A. J. 276 Stegagno, L. 42 Stein, I. 216 Stein, S. 309, 317 Steinke, W. R. 188 Steinling, M. 275 Steinthal, P. 162, 170 Steinvorth, S. 424 Stella, G. 127

Author index Stemmer, B. 101, 102, 105, 149 Stephan, K. M. 289, 290 Stepniewska, I. 32 Stern, C. E. 288, 427 Stern, E. 275 Stern, M. B. 455 Stern, Y. 450 Sternberg, R. J. 17 Sternberg, S. 332 Sterzi, R. 292, 298, 308, 315, 317, 318, 320, 388 Stewart, E. 64 Stewart, J. D. 268, 269, 275, 276 Stewart, W. F. 458 Stiles, W. S. 233 Stilwell-Morecraft, K. S. 42 Stoll, G. 311, 313 Stone, J. S. 128 Stone, L. V. 128 Stone, V. 402 Stracciari, A. 308 Strauss, A. 220 Strauss, H. 52 Strauss, M. E. 502 Strauss, M. S. 201 Streb, J. 362 Strohner, H. 237 Strube, E. 309, 317 Studholme, C. 481 Stuss, D. T. 379, 380, 388, 394, 397, 400, 402, 456, 476, 481, 483, 484, 496 Sugai, T. 420 Sugar, O. 25 Sugishita, M. 293, 295 Sugiura, M. 273 Sullivan, E. V. 420, 441, 461 Sumida, T. 293, 296 Summerfield, J. 359 Sur, M. 286 Surma-Aho, O. 400 Suzuki, H. 38 Suzuki, K. 241, 296, 297 Suzuki, W. A. 42, 413 Swanson, J. M. 339 Swick, D. 338, 415, 426 Swinburn, K. 140 Symons, A. 493 Syrota, A. 288 Szalai, J. P. 310, 312 Tabatabaie, S. 122 Tabert, T. H. 427 Taipale, M. 127 Taira, M. 34 Takagi, K. 476, 477 Takeda, N. 420 Talbot, J. D. 288, 289 Talbot, P. R. 496, 503 Tallal, P. 130, 131, 271 Tallon-Baudry, C. 366

Talton, L. E. 429 Tamaru, F. 268, 274, 275, 276 Tan, L. H. 127, 131 Tanaka, K. 35 Tanaka, Y. 34, 267, 268, 270, 271 Tang, C. Y. 427 Taniguchi, S. 484 Tanila, H. 425 Tansy, A. P. 142 Target, M. 336 Tatsukawa, K. 311 Taylor, A. E. 455, 461 Taylor, A. M. 258, 259, 293 Taylor, K. 367 Taylor, L. 298 Taylor, M. J. 130, 147 Teasell, R. 155 Tegnér, R. 210, 320 Tekin, S. 491, 502, 503 Templeman, F. D. 454 Teramura, K. 275 Termine, C. 127 Terry, R. D. 459 Testa, H. J. 503 Tettamanti, M. 68, 142, 143, 144 Teuber, H. L. 11, 52, 231 Thaut, M. H. 195 Théroux, A. M. 96 Thiebaut de Schotten, M. 313 Thiel, A. 138, 188 Thiercelin, D. 138 Thioux, M. 209, 216, 220 Thiran, J. P. 275, 276 Thomas, A. 128, 498 Thomas, K. M. 336, 343 Thompson, J. 340 Thompson, K. G. 364 Thompson, R. D. 272 Thompson, S. A. 473, 482 Thompson-Schill, S. L. 67, 415, 426 Thomson, G. 17 Thron, A. 310 Thurstone, L. L. 17 Tian, B. 38 Tiberti, C. 491, 502 Tiitinen, H. 366 Tippette, L. J. 454 Tissot, R. 237 Titchener, E. B. 331 Todd, E. C. 420 Todd, R. D. 385 Toga, A. W. 491, 499 Tomaiuolo, F. 308, 310, 313 Tomer, R. 393, 402 Tomoeda, C. K. 455, 480 Tompkins, C. A. 95 Tootell, R. B. 354 Touyeras, B. 142 Towne, B. 342 Trabucci, C. 454

537

538

Author index

Trainor, R. J. 384 Tralli, A. 475 Tramo, M. 188, 196, 268, 273, 277 Tranel, D. 338, 380, 414, 420 Trappl, R. 148, 154 Trauner, D. A. 272 Treadwell, J. 447 Tredici, G. 174 Trehub, S. E. 185, 186 Treisman, A. 252, 257, 352, 356, 359, 363 Treue, S. 356 Trieb, T. 67 Troiani, V. 403 Trojano, L. 450 Trojanowski, J. Q. 481, 483 Trosset, M. W. 455 Tröster, A. I. 455 Trousseau, A. 76 Tsal, Y. 340 Tseng, C. 100 Tsivkin, S. 213 Tsuchiya, H. 365 Tsuyuguchi, N. 311 Tsvetkova, L. S. 188 Tucker, D. M. 84, 89 Tudela, P. 357, 361 Tuinier, S. 420 Tulving, E. 388, 416, 424, 425, 426, 427, 437, 438, 439, 444, 451, 452, 456, 460, 472 Tupper, A. 148 Turconi, E. 209 Turken, A. U. 242, 338 Turner, J. 269 Turner, R. 384 Tyler, L. K. 243 Tzortzis, C. 188 Tzourio, N. 220 Tzourio-Mazoyer, N. 216, 420 Ulatowski, J. A. 310 Ullman, S. 251 Umeda, Y. 484 Ungerleider, L. G. 67, 251 Urbanski, M. 313 Uske, A. 312 Uylings, H. B. M. 31 Vaadia, E. 38 Valdes-Sosa, M. 354 Valenstein, E. 84, 89, 170, 308, 309, 311 Valero-Cabré, A. 313 Vallar, G. 56, 122, 292, 308, 309, 310, 311, 312, 313, 314, 315, 317, 318, 319, 320, 321 Vance, S. C. 392, 420 Vandegeest, K. A. 338 Van de Moortele, P.-F. 215, 216, 220 Van der Linden, M. 211, 212, 213, 450 Vandevivere, J. 499, 503 Van Eeckhout, P. 141, 187, 188 Van Essen, D. C. 355

Vanhalle, C. 102 Van Harskamp, N. J. 213 Van Heugten, C. M. 149 Van Hoesen, J. W. 42 Van Lancker, D. 195, 272, 273 Van Mier, H. 68 Vannier, M. 385 Van Paesschen, W. 424, 425 Van Swieten, J. C. 503 Van Veen, V. 340 Van Velzen, J. 365 Van Vleet, V. M. 313 Van Voorhis, S. T. 353 Van Zijl, P. C. 26 Vargha-Khadem, F. 424, 425 Varley, R. 243 Varma, A. 473, 474, 496 Varney, N. 53 Vecera, S. P. 252 Veenema, S. 20 Veeraraghavan, S. 133 Velasco, F. 312 Velasco, M. 312 Venneri, A. 473 Verfaellie, M. 165, 166, 176, 315 Verga, A. 322n1 Verguts, T. 221n4 Verhey, F. R. 420 Verhoeven, W. M. 420 Vermeulen, J. 154 Vernet, O. 276 Verstichel, P. 205 Vervaet, A. 498 Viader, F. 138, 267, 274, 275, 317 Vidal, F. 365 Videen, T. O. 288 Vidyasagar, T. R. 252 Vignolo, L. A. 53, 93, 94, 127, 137, 138, 141, 147, 148, 154, 163, 185, 231, 237, 262, 268, 274, 275, 276, 298, 307, 308, 321, 331, 333, 334, 420, 448, 459 Vikingstad, E. M. 140 Vilkki, J. 312, 400 Villalpando, J. M. 498 Villemure, J. G. 275 Villringer, A. 63, 64, 66 Vinters, H. V. 491, 502, 503 Visser, P. J. 420 Vista, M. 148, 154 Vitali, P. 142, 143, 144 Vitolo, F. 124 Vizueta, N. 343 Vloeberghs, E. 493, 502, 503 Vogel, A. 503 Vogel, E. K. 356, 360, 361, 363, 364 Vogler, G. P. 342 Vogt, B. A. 42 Vogt, C. 286 Vogt, O. 286 Volle, E. 313

Author index Volpe, B. T. 309, 317, 334 Volteau, M. 491 Von Cramon, D. 254, 420 Von Frey, M. 292 Von Monakow, C. 174, 311 Von Stockert, T. 243, 274, 275 Vygotsky, L. S. 337 Wade, D. 42, 317, 392, 393 Wade, E. 453 Wagner, A. D. 36, 415, 426 Waldemar, G. 503 Waldron, E. M. 242 Walker, J. A. 341, 343 Wallace, M. N. 35 Wallace, W. T. 189 Wallesch, C. W. 231, 309 Wallicke, P. A. 441 Walsh, V. 216 Walter, W. G. 332, 365 Wang, C. 342 Wang, E. 270 Wang, K. 342 Wang, N. 366, 367 Wang, R. 26, 32 Wang, X. 271 Wang, Y. 128 Want, S. C. 243 Wapner, W. 98, 101, 102 Warburton, E. 140 Ward, A. A. 25 Ward, C. 455 Ward, R. 364 Warren, J. D. 38 Warrington, E. K. 19, 122, 204, 210, 211, 220, 234, 239, 241, 243, 258, 259, 293, 299, 414, 437, 444, 453, 471, 472, 475, 476, 483 Wartenburger, I. 63, 64 Washburn, D. A. 339 Watabe, S. 275 Waters, G. 448 Waters, N. S. 131 Watkins, K. E. 424, 425 Watkins, L. H. 451 Watson, R. T. 169, 171, 172, 174, 176, 179, 272, 308, 309, 313, 317, 319, 320, 458 Watson, R. W. 451 Webb, W. G. 480 Weber, T. A. 354 Weber-Luxenburger, G. 138 Webster, D. D. 451 Wechsler, E. 148 Weekes, B. S. 116, 120, 125 Weeks, R. 296 Wei, T. C. 427 Weiller, C. 139, 140, 141, 310 Weinberger, D. R. 77 Weiner, M. 481, 503 Weingartner, H. 392, 420 Weinstein, E. A. 94

539

Weinstein, S. 231 Weintraub, S. 414, 476, 477, 498 Weis, J. 461, 484 Weiskrantz, L. 414, 437, 444 Weiss, D. G. 148, 155 Weiss, P. H. 37, 171 Welch, K. M. 140, 172 Welkowitz, J. 96 Welsh, K. 169 Wepman, J. M. 148 Werner, H. 220 Wernicke, C. 25, 51, 52, 77, 78, 79, 80, 81, 82, 123, 162, 231, 253, 267, 294, 310, 312 Wertheim, N. 277 Wertz, R. T. 148, 155 West, R. 419, 448 Westerberg, H. 340 Westheimer, G. 357 Westmacott, R. 473 Weyers, M. 171 Whalen, J. 213 Wharton, C. M. 215 Wheeler, M. A. 456 Wheeler, M. E. 426 Whelan, H. 320 White, D. A. 140 White, K. 142 Whitehouse, P. 232 Whitwell, J. L. 481, 503 Whurr, R. 149, 155 Whyte, J. 388 Wickelgren, W. A. 414 Wiese, H. 219 Wigg, K. G. 127, 132 Wiggs, C. L. 67 Wijers, A. A. 356 Wilding, E. L. 357, 364 Willemen, J. J. 127 Williams, G. 481, 483, 503 Williamson, D. J. 178, 320 Willmes, K. 140, 148, 310 Wilson, B. A. 122, 241, 260, 420 Wilson, F. A. W. 418 Wilson, J. 455 Wilson, R. 445, 449 Wilson, R. S. 449, 451 Wilson, S. J. 188 Wiltgen, B. J. 429 Windischberger, C. 39 Winner, E. 103 Winocur, G. 414 Winter, A. L. 332, 365 Wise, R. J. S. 36, 67, 140, 277, 420, 421 Witte, O. W. 311, 313 Witton, C. 188, 268, 274, 276, 277 Wityk, R. J. 310 Wixted, J. T. 456 Woldorff, M. G. 364 Woll, G. 237 Wolpert, I. 255

540

Author index

Wong, C. 459 Wood, C. C. 349, 350, 361 Wood, E. 425 Wood, F. B. 365 Woodman, G. F. 356, 363, 364 Woodruff, P. W. 96 Woodruff-Pak, D. S. 419 Woods, R. P. 288 Woolsey, T. A. 27 Woolson, R. F. 309, 311, 312, 315, 317, 320 Worden, M. S. 361, 366, 367 Worsley, K. J. 66 Worthley, J. S. 453 Wright, S. P. 416 Wurtz, R. H. 334 Wynn, K. 201 Wyszecki, E. 233 Xu, Y. 270 Xuereb, J. H. 480, 483, 484, 485 Yamadori, A. 186, 241, 267, 268, 270, 271, 274, 275, 276, 296, 297 Yamagata, S. 361 Yamaguchi, N. 475 Yamaguchi, S. 361, 365, 367 Yamamoto, H. 296 Yanagisawa, N. 293, 295 Yasuda, M. 499 Yeni-Komshan, G. 270 Yenkosky, J. 272 Yeterian, E. H. 318

Yetkin, F. Z. 172 Yilmazer, D. 420 Yin, W. G. 125 Yoneoka, Y. 420 Yoshida, M. 267 Young, A. C. 142 Young, A. W. 231, 421 Young, R. C. 492, 493 Zafiris, O. 273 Zago, L. 216 Zahn, R. 140 Zahn, T. P. 380, 392 Zalla, T. 386 Zangwill, O. 52, 147, 177, 231 Zarahn, E. 60 Zatorre, R. J. 36, 38, 273 Zeki, S. 254, 355 Zesiger, P. 219, 269 Zhao, Z. 422, 426, 428 Zhuo, Y. 366 Ziebell, M. 503 Zielinski, B. A. 38 Zihl, J. 254 Zilbovicius, M. 141, 187, 288 Zilles, K. 31, 37, 171, 273 Zilli, T. 317 Zola, S. M. 420, 424, 425 Zola-Morgan, S. 42, 414, 425 Zuendorf, G. 503 Zuffi, M. 475 Zurif, E. 232, 237, 243

Subject index

Acalculia 4, 203, 211 Acetylcholine 414 Achromatopsia 253 Addenbrooke’s Cognitive Examination 497 Aging 341–2, 418–19, 427, 438, 440, 445, 448–9, 453, 456–8, 461–2 Agnosia 52, 313 apperceptive 250–1, 262, 277, 293 associative 250–1, 260–2, 277, 293 auditory 11, 267–78, 478 digital 220 integrative 262 multimodal 286 object 178 primary progressive (PPA) 472, 477 tactile 285, 291, 293–7 visual 52, 89, 249–63 visual associative 471, 476, 477 visual form 254–5 Agrammatism 151–4 Agraphia 12, 39, 52, 96, 117, 118, 121, 123 apraxic 123 Ahyloagnosia 293–4 Akinesia 162, 387, 389, 391 Alexia 12, 39, 52, 113, 118, 121, 123, 209, 253 spatial type 96 “Alien hand” 387, 389–90 Alzheimer’s disease (AD) 55, 162, 179, 258, 277, 341–2, 401, 411, 414, 420, 422, 441–2, 445–6, 449–50, 453–5, 458–61, 477, 480, 482, 491–503 Ambidextrals 93 Ammon’s horn 413 Amnesia 52, 84, 387, 411, 412, 413, 414, 440, 443, 445, 459 anterograde 421, 437 global 413, 419–21 retrograde 421, 424, 437 Amorphoagnosis 293–4, 297 Amusia 188, 191, 267, 271, 274, 277–8 Amygdala 41, 337, 338, 343, 384, 385, 393, 401, 413, 414, 421–3, 427–8, 481 Amygdalar-hippocampal circuit 428 “Anarchic hand” 387, 390, 391

Aneurysm 386, 393 Angular gyrus 39, 40, 118, 311, 313 Anomia 142, 143, 151, 152, 193, 295, 472, 473, 479 spontaneous speech 85–6 Anosognosia 315–17, 400, 459 Anterior cingulate gyrus 85, 337, 383, 385 Anterior cingulate region 336–9, 342, 390, 391, 502 Anterior language region 31 Anterior parietal lobe syndrome 292 Anterior parietal region 53, 286 Anterior temporal lobe 393 Anthropology 18 Aphasia 4, 7, 9, 39, 51–2, 56, 75–91, 93, 97, 100, 103–6, 113, 118, 138, 141, 170, 188, 191–3, 204, 208, 213, 231, 242, 274, 308, 309, 313, 314, 471 acquired epileptiform 269 adynamic 85–6, 87 amnesic 12, 52 anomic 83, 84, 87, 89, 231–2 Broca’s 11, 12, 53, 75–7, 81–2, 87, 150, 232, 386 and colour 233–4, 237–40 conduction 51, 78–9, 81, 86, 87, 88, 141, 150 crossed 93 definition of 105 expressive 51 extrasylvian motor 85 global 51, 153 jargon 77, 151–2 latent 94 and lesions 53, 150 nonfluent 141, 386, 387, 481 nonoptic 87, 89 optic 87, 89 in polyglots 52 primary progressive (PPA) 472, 480 progressive 480, 481 progressive fluent 485 recovery from 137–44 rehabilitation from 147–56, 307 semantic 480

542

Subject index

Aphasia – Contd. sensory 51, 480 and singing 186–7 spontaneous recovery from 147–8 subcortical 53, 309 tactile 295, 296 thalamic 53 transcortical 12, 81–5, 87, 89, 153, 387, 480 variability of 150–3 Wernicke’s 12, 77–8, 81, 87, 150 Aphasia therapy 147, 153 effectiveness of 150 efficacy of 147–50, 155–6 Aphasiology 4, 123 Aphemia 76 Apolipoprotein E 503 Apraxia 4, 11, 52, 53, 170, 173, 313, 386, 387 conceptual 161, 177–80 definition of 161–2 dissociation 161, 175–6, 179 forelimb 161–80 gait 162 ideational 161, 176–7, 180 ideomotor (IMA) 161, 165–8, 170–80 innervatory 163–5 limb-kinetic (LKA) 161, 162, 163–5, 180 melokinetic 162, 163–5 oculomotor 162 speech 162 testing for 167–8 Aprosodia 97, 268, 271–2, 386, 387 Arabic numerals 205–12, 219, 221n1 Arabic script 118 Architectonic structures 20, 26, 34 Arcuate fasciculus 26, 27, 30, 31, 34, 38, 42, 81 Aristotle 437 Arithmetic 201 asemantic route in 212–13 non-symbolic 201 semantic route in 213 symbolic 201, 205–10, 215–20 presymbolic 217, 218, 220 Art 5 Articulation 105 Articulatory module 90 Articulatory processing 35–6, 37 Ascending sulcus 37 Aspontaneity 496, 504 Association fiber pathways 25–7, 30, 31, 33, 40–1 Association Network Test 339, 341, 342, 343 Astereognosis 52 Asymbolia 170, 291, 293 Attention 2, 5, 31, 38, 52, 53, 55, 63, 251, 312, 331–43, 351–67, 384, 385 executive 340, 343 impairment of 386, 387 selective 352–68 spatial 31, 312, 315, 353–4, 356 “spotlight” of 363

temporal orienting of 357–8 visual 251–2, 255–8 Attention deficit hyperactivity disorder (ADHD) 340–1, 386 Attention network test 340 Attentional blink 361–2 Attentional control 365, 367–8 Attentional modulation 354, 356, 360, 364, 366, 368 Attentional selection 352–68 gain control in 364–5, 366–7 locus of 359–63 Auditory association cortex 77, 87 Auditory processing 130, 132 Autism 341, 342 high-functioning 386 Autonoesis 416 Autoradiographic method 27 Ballismus 161 Basal forebrain 387, 393, 414, 419, 420 Basal ganglia 76, 85, 87, 174, 308–13, 315, 317–20, 342, 384, 451, 502 Base-10 semantic system 207, 208, 217, 218, 220 Bayley, John 411 Behavioural Pathology in Alzheimer’s Disease Rating Scale (Behave-AD) 492, 493, 495, 499, 500–1, 503 Bell Curve, The, 17 20 Bilinguals 57, 63, 64–7 Binet, Alfred 18 Bipolar disorder 391 Blood circulation 54 Blood oxygenation level dependent effect (BOLD) 56, 57, 142, 398, 400 Borderline personality disorder 343 Boston Naming Test 494, 498, 500 Bourne Supremacy, The 411 Bradykinesia 196, 387 Brain anatomy 2, 25, 51, 53 and language 26 Brain–behaviour relationship 1–2, 51, 52 Brain damage 11, 12, 39, 179, 204, 212, 241, 267, 271, 292, 294–7, 307, 311, 312, 320, 419–21, 462 Brain–function relationship 67 Brain injury 1–2, 51, 85, 137, 272, 292, 386 Brain lesions 10, 79, 105, 188 Brain regions 1–2, 25–43, 150 interactions of 58 Brainstem 384 Brainstem pyramids 161, 164 Broca’s area 26, 31, 32, 34, 35, 42, 53, 57, 67, 77–8, 80, 82–3, 85, 86, 88, 90, 118–19, 141, 142, 143, 277, 290, 383, 384, 411 Brodmann’s area 161, 164, 286, 287, 314, 383, 384, 390, 391, 415 Bromocriptine 391

Subject index Calcarine sulcus 353 Calculation 201–21 Callosal disconnection 169, 175, 179, 387 Capgras syndrome 387 Cathecol-O-methyltransferase 503–4 Caudal cingulate region 42, 43 Caudal parietal lobe 179 Caudal superior temporal gyrus 27 Caudate nucleus 174, 317, 443 Central executive (CE) 447, 448 Central sulcus 286, 287, 383 Centre of auditory memories 118–19 Centre of visual memories 118–19 Cerebellum 342, 384, 419, 426 Cerebral blood flow 54, 55–6, 57, 342 Cerebral cortex 25, 40, 77, 128, 130 incipient 128 cerebral commisurotomy 298 Cerebral edema 138 Cerebral peduncle 161 Chinese language 132 Chinese script 118, 124, 131 Cholinesterase inhibitor 492 Chomsky, Noam 105 Chorea 161 Cingulate cortex 34, 39, 308, 385 Cingulate gyrus 315, 337 Citizen Kane 411 Coding hypotheses 99 Cognitive impersistence 86 Cognitive-linguistic disorders 104 Cognitive neuropsychology 2, 113, 513–14 Cognitive theory 58 Cohen-Mansfield Agitation Inventory (CMAI) 492–3, 495, 501 Coin-rotation task 163–4 Collateral sulcus 413 Computerized tomography (CT) 11–12, 53, 307, 309 Conceptual-semantic field 80–5, 87, 89, 90 Confabulation 387, 393, 459–60 Confabulation Battery 460 Conscience 338–9 Contralateral somatosensory cortex 285 Controlled Oral Word-Fluency Test 87 Convexity premotor cortex 164, 173–4 Cornell Scale for Depression in Dementia (CSDD) 492–3, 495, 499, 501 Corona radiata 309, 311, 317 Corpus callosum 118, 121, 165, 168–9, 174, 385, 390, 391, 413 Corpus striatum 75 Cortical blindness 52 Corticobasal degeneration 162, 204, 477, 478 Corticolimbic system 440 Corticospinal system 161, 164, 165 Corticostriatal system 440 Cortico-striatal-thalamo-cortical loop 455 Counting 202–4

543

Cribiform plate 385 Crovitz test 460 Dali, Salvador 411 Data analysis 61 Deafness cerebral 267 cortical 267 post-access 269 pre-access 269 word 78, 79, 81, 87, 267–71 word form 269 word meaning 269 Deep dysphasia 86, 87, 88 Deftness 163–5 Delusions 387, 393, 492, 499 Dementia, 5, 55–6, 179, 204, 438, 440, 446, 456, 458, 492, 503, see also Frontotemporal dementia, Semantic dementia of Alzheimer type (DAT) 204, 208, 209–10, 480–1 behavioural and psychological signs and symptoms of (BPSD) 491–3, 498, 504 mixed (MXD) 493, 498, 499, 502–3 semantic 5, 86, 243, 420 Dementia lacking distinct histology 477, 484 Dementia with Lewy bodies (DLB) 492, 493, 499, 502 Dentate fascia 483 Dentate gyrus 413 Deoxyhemoglobin 56–7 Depression 385, 391, 459, 491–3, 495, 499, 501–2 Diagonal band of Broca 383 Diaschisis 138–9, 311, 139 Diencephalic structures 419, 420, 445 Dietary hyperactivity 496 Diffusion tensor imaging 32, 481 Disconnection syndromes 312 Discourse abilities 95, 100–1, 104, 106 Disinhibition 386, 387, 491, 492, 493, 496, 498 Donepezil 414 Dopamine 339, 391, 502 Dopamine receptor D3 (DRD3) 503–4 Dorsal prefrontal areas 30 Dorsal root ganglia 285 Dorsolateral frontal lobe 85, 87 Dorsolateral prefrontal cortex 35, 384, 386, 388, 417, 418 Dorsomedial nucleus 414 Double dissociation 11, 207, 241, 276 Dysarthria 194, 195, 386, 387 Dyscalculia 203, 210 Dysgraphia 117, 123–4 acquired 113 allographic 124 apraxic 124 deep 118, 120, 121, 124

544

Subject index

Dysgraphia – Contd. neglect 122 phonological 118, 123–4 surface 118, 123, 475 Dyslexia 4, 118–22, 308 acquired 113, 116 attentional 258 deep 116, 119–21 developmental 127–33 and genetics 127–8 neglect 122, 316 neuroanatomical substrates of 128–30, 133 and neuron size 130 phonological 116, 121, 131, 132 surface 116, 120, 475, 479 susceptibility to 127–8 Dysprosodia 97 Dysthymia 491 Echo planar imaging 56 Echolalia 472, 496 Ectopia 128–31 Education 20 Electroencephalogram (EEG) 349–51 and attention 351–67 Emotion 337, 384–7, 389, 391, 392, 412, 421, 496 social 401–3 Emotional processing 141, 392, 393 Empathy 338, 387, 392, 402, 403 English 114 Entorhinal cortex 413, 424 Epilepsy 286, 412, 437 Epileptic seizures 269 Episodic buffer 417 Event-related potentials (ERPs) 349, 353, 360, 364 Executive Interview (EXIT) 497 Experimental psychology 52, 202, 331, 513 Experimental task design 59–63, 67 block designs 59–60 event-related, Extreme capsule 30, 31, 36, 37 Fetal alcohol syndrome 386 Forgetfulness 458 Fragile X 386 Free recall 36 French 114, 124 Frontal Assessment Battery (FAB) 494–8 Frontal Behavioural Inventory, (FBI) 497 Frontal cortex 27, 141, 171, 445 Frontal lobe 29, 34, 39, 308, 320, 379–404, 482, 491–504 atrophy of 481 damage to 51, 75–6 Frontal lobe syndromes 379–80, 385–94, 403, 448 lateral 386–9 mesial 387, 389–91 ventral 387, 392–4

Frontal lobectomy 419 Frontal operculum 77, 87 Frontal-parietal disconnection 391 Frontal parietal region 53 Frontotemporal dementia (FTD) 204, 386, 401, 403, 477, 481–4, 491, 493, 496–7, 502–3 frontal variant (fvFTD) 473–4, 478 and motor neuron disease 483 temporal variant 483 Frontotemporal lobar degeneration (FTLD) 484–5 Functional connectivity 58 Functional integration 58 Functional specialization 58 Fusiform face area 262 Fusiform gyrus 67, 252, 426, 481, 483 Gage, Phineas 379–80, 392 Gene dysfunction 127 Genetics 339–41 German 114, 124, 504 Gerstmann syndrome 213, 215, 219 Global Deterioration Scale (GDS) 493, 494, 498, 500 Globus pallidus 174, 342 Goal-directed behaviour 379, 381, 387, 389, 391, 392, 394, 397, 449 Grammatical judgment 65 Grammatical processing 64, 66–7 Granular insula 286 Grapheme-to-phoneme correspondence 114, 125 Graphemic processing 103–8, 117–22, 124 Grey matter 310 Gyrus ambiens 413 Gyrus rectus 383, 391 Gyrus semilunaris 413 Hallucinations 492, 499 Hand motor center 119 Hazard function 357 Head trauma 386, 420 Hearing acuity 267 Hebrew script 118, 124 Helm Elicited Language Program for Syntax Stimulation (HELPSS) 153–4 Hemianaesthesia 285, 292, 315 Hemianopia 89, 121, 315 Hemiparesis 386, 387 Hemiplegia 76, 120, 170, 315–17 Hemiasomatognosia 316 Hemispatial neglect 387, 388 Hemispheric asymmetry 272, 307, 309 Hemispheric dominance 12, 51, 52, 93–106, 140, 142–3, 216, 272, 276, 419 Hemispheric specialization 11, 141, 165, 168–9, 179, 180, 187, 194, 243, 275, 298, 299 Hemodynamic response 60

Subject index Hemoglobin 56 Heritability 339 Herpes simplex encephalitis 386, 420, 485 Heschl’s gyrus 267, 269, 273 Hierarchic Dementia Scale (HDS) 493, 494, 498, 500 Hippocampal formation 67, 413 Hippocampus 68, 384, 413, 414, 420, 421, 423–5, 428, 473, 484 Homophone test 82–3 Homunculus sensitivus 286 Horizontal sulcus 37 “How” programs 161 Human genome 132 Humour, sense of 19, 100, 102 Huntington’s disease (HD) 442, 443, 446, 451, 456, 461 Hydrocephalus 386 Hyloagnosis 291, 295, 297 Hypersexuality 496 Hypokinesia 316 directional 320 Hypometabolism 319, 503 cortical 310 Hypoperfusion 319, 503 cortical 310 Hyposexuality 496 Hypothalamus 384, 385, 393 Hypoxia 420 Idiot savants 18 Illusory conjunctions 252 Indirect speech acts 102 Infarction 169, 310 cerebral 162, 169, 179 incomplete 138, 310 thalamic 312 Inferences 101 Inferential processing 403 Inferior frontal gyrus 26, 31, 34, 140, 143, 290 Inferior frontal operculum 76 Inferior frontal sulcus 37 Inferior intraparietal region 214 Inferior mesial cortex 387 Inferior olivary nucleus 484 Inferior parietal cortex 32, 276, 313 Inferior parietal lobule/lobe 32, 34, 35, 37, 39, 40, 41, 172, 314, 384 Inferior prefrontal regions 130 Inferior temporal gyrus 67, 483 Inferior temporal lobe 57 Insula 76, 276, 277, 287, 290, 385, 401 Insular cortex 76 Intelligence 17–22, 53, 396, 398 emotional 19, 396 fluid 398 general (g) 17–18, 20, 251, 340, 380, 398 musical 20 spatial 20 Intelligence quotient 17, 18, 20, 380, 398

545

Intelligence theory 17–18 Intentional system 85, 86 Interconceptual/intraconceptual hypothesis 99–100 Interhemispheric commisures 165, 175 Interior frontal lobe 87 Internal capsule 161, 309, 311, 317, 318, 320 Intracellular recording 334 Intracranial hypertension 138 Intralaminal tract 414 Intraparietal sulcus 32, 216, 289, 290 Intrarhinal sulcus 413 Ischaemic penumbra 310 Isolation transcortical aphasia 89 Italian 114, 124 Japanese script 118, 124 Jargon phomemic 151–2 semantic 87, 90 verbal 151 Johns Hopkins University Dysgraphia Battery 124 Kaufman Brief Intelligence Test (K-BIT) 340 Kinaesthesia 291, 294 Knowledge conceptual 177 production 177 shared 102, 103 Korsakoff syndrome 420 Kussmaul’s model 82–5, 89, 90–1 Landau–Kleffner syndrome (LKS) 269 Language 25–43, 51, 53, 55, 58, 91, 106, 122, 202, 220, 309 acquisition of 68, 424 and cognitive processes 38–43 evolution of 35 and the left hemisphere 93, 187 localization of 53 and the right hemisphere 93–106, 187 and thought 231–7, 241 Language disorders 12 and multiplication impairment 213 Language impairment 93, 231, 480 and lesions 93–106, 243 Language processing 37, 42, 64–6, 67, 95 Language recovery 137–44, 188 three-stage model of 137–8 Latency modulation of perceptual analysis 364–5 Lateral frontal region 383 Lateral geniculate nucleus 130 Lateral inhibition 98 Lateral occipital region 252, 262 Lateral prefrontal cortex 338, 384 Learning disabilities 18

546

Subject index

Learning systems taxonomic 237, 239–43 thematic 237, 239–43 Left-handedness 93, 168, 179, 419 Left inferior prefrontal cortex 415, 426 Left parietal lobule 216 Left precentral gyrus 220 Left prefrontal cortex 274 LeMo test 122 Lenticular nucleus 317 Lesion-behaviour method 51–3, 58, 67, 76, 79, 113 Lesions 75–9, 81, 82, 84, 85–6, 87, 93, 113, 139–43, 150, 164, 169, 212, 252, 290, 309, 311, 319, 331, 336, 394–5, 400, 421, 428, 445, 448, 461, 471 of amygdala 423 bilateral 270, 421 bilateral posterior 258 bilateral subcortical 276 bitemporal 267 callosal 169, 170, 176 collicular 334 cortical 103, 243, 274, 285, 291, 308, 311, 313, 314, 315, 317, 414 focal 312, 313 frontal 321, 379, 461 left-hemisphere 93, 100, 104, 120, 168, 170, 176, 203–4, 213, 276, 292, 298, 307, 341 left temporal 269 left unilateral 270–1 medial frontal 172–3 medial temporal lobe 420 nigrostriatal system 309 parietal 171, 172, 297 parieto-occipital 257 perisylvian 77 posterior 262 posterior parietal 210, 278, 311 prefrontal 379–81, 388, 392, 393, 395–6, 414 premotor 171, 172 pulvinar 334 right-hemisphere 93–106, 203–4, 275, 276, 292, 298, 311, 315, 318, 322 right-parietal 334 subcortical 174, 274, 309, 310, 311, 313, 315, 317–18 superior collicular 309 temporoparietal 151, 271, 341 thalamus 309 virtual 313 Levodopa 499 Lexical errors 206 Lexical semantics 105, 117, 140 Lichtheim’s model 80–5, 89, 90–1 Limbic system 41–3, 337, 413 Lingual gyrus 67 Linguistic ability 34 Lissencephaly type I 128 Localizationalism 52, 75, 87

Logographic scripts 118 Logorrhoea 77, 496 Longitudinal fasciculus inferior 310 superior 27, 31–3, 37, 38–40, 310 Loudness discrimination 276 Macaque 25–9, 339 Magnetic resonance imaging (MRI) 41, 53, 56, 130, 138, 268, 392, 481–2, 484 event-related functional (er-fMRI) 142 functional (fMRI) 54, 56–61, 139–44, 164, 289, 290, 351, 398, 412, 415, 425 Magnetoencephalogram (MEG) 350–1 Márquez, Gabriel García 411 Medial dorsal nucleus 312 Medial frontal lobe 85, 87 Medial frontal region 383 Medial prefrontal areas 31, 41, 42 Medial temporal lobe (MTL) 412–4, 419, 420, 426, 437, 445 Medial thalamus 85 Melodic intonation therapy (MIT) 141, 187, 193, 195 Memento 411 Memory 5, 55, 63, 251, 269, 293, 359, 384, 388, 392, 411–29, 437–62, 496 and aging 418–9, 427, 438, 440 and arithmetic 213 anterograde 473 autobiographical 439, 473 declarative 412, 416, 424, 439 deficits in 491 emotional 421–5, 427–8 encoding processes in 426 episodic 412, 424–5, 437, 439, 445, 451, 456–61, 473, 480 event 439 factual 439 generic 439 hierarchical model of 459 implicit 412, 414 knowledge 439 lexical 296 long-term (LTM) 36, 194, 296, 359, 397, 413, 414, 416–17, 447–9 neuroanatomy of 412–4 non-declarative 412, 414, 416, 439 non-spatial 425 olfactory 438 personal 439 phonological working 143 primary 439, 447–51 procedural 439–43 prospective 414, 419 recognition 438, 460–1 retrieval processes in 426 role of hippocampus in 423–5 semantic 293, 296, 412, 415, 416, 424, 437, 439, 451–6, 458, 459, 472, 481

Subject index short-term 117, 202, 215, 269, 414, 416, 417, 439, 447–51 source 457, 460, 461 spatial 42, 425, 438 verbal 438, 473 verbal declarative 42 verbal working 67, 388 working 42, 77, 337, 362, 363, 387, 403, 414, 417, 427, 439, 447–51, 473 Memory disorders 412 Memory systems 438–9 Mesial gyrus rectus 383 Mesial prefrontal cortex 401 Metacognition 400–1 Metalinguistic processing 38–43 Metaphorical meanings 97–8 Microgyria 128–9 Middelheim Frontality Score (MFS) 495, 496–500, 502–4 Middle longitudinal fasciculus 40–1 Middle temporal regions 276 Mild cognitive impairment (MCI) 491 Mind–brain relationship 2, 9 Mindblindness 52, 250 Mini-Mental State Examination (MMSE) 493, 494, 498, 499, 500, 502 Minority Report 411 Mnemonic processing 42 Modalities 96–7 Modular functional architecture 206–7 Modularity 75, 77 Morphoagnosis 291, 295, 296, 297 Morphosyntax 105 Motor center of word articulation 119 Motor cortex 76, 81, 87, 180 Motor impersistence 386, 387 Motor neglect 316, 317 Motor neuron disease 477, 483–4 Motor perception 253–4 Motor processing 153 Multiple intelligence (MI) theory 19–22 Multiple sclerosis 386 Murdoch, Iris 411 Music 4, 11, 21, 188–90, 277–8 Music therapy 194, 195–6 Musicians 188, 190 Mutism 39, 387, 389, 391, 472, 476, 496 akinetic 85 Myoclonus 161 Naming disorders 242–3 Necroscopy 12 Neologisms 77, 78, 87, 120 Neo-Piagetians 337 Neural circuitry 25–43 Neural networks 2, 42, 63, 88, 99, 337, 382–5, 403 Neural synchronization 366–7 Neurobehavioural syndromes 51

547

Neuroimaging 2, 3, 125, 139, 273, 308, 335–6, 339, 418, 427 functional 35–9, 42, 54–63, 67, 68, 95, 137–44, 268, 288–90, 398–9, 402, 425–8, 481 structural 53, 67, 481 Neurolinguistics 144 Neuromodulators 339 Neuronal excitability 138 Neuronal migration 127–8, 131–2 Neuronal sprouting 138 Neuropsychiatric Inventory (NPI) 492–3 Neuroreceptors 53 Neuroscience 2 Neurotransmitters 53 Nonaphasic acquired language disorders 104 Nonhuman primates 25, 27–9, 31–6, 38, 41, 254, 286–9, 313, 333, 334, 339, 354, 356, 364, 366, 425 Nonselective recruitment 427 Non-verbal reasoning task 235–7 Norepinephrine 332, 503 Nucleus accumbens 383, 385 Nucleus basalis 385, 414 Number processing 201–21 Numerosity estimation 216 Object-decision test 447 Object recognition 87, 288, 291–3 tactile (TOR) 292–3, 299 Occipital cortex 141, 171, 426, 446 Occipital lobes 89, 130, 250, 254, 313 lesions of 52, 121 Occipital parietal region 177 Occipital visual centre 119 Olfactory nerve 385 Olfactory tracts 383 Optic chiasm 413 Orbital cortices 387 Orbital frontal cortex 31, 41, 42, 502 lesions of 41, 423 Orbital gyri 383 Orbital prefrontal cortex 401 Orbitofrontal lobe 57 Orbitofrontal region 403 Orthographic input lexicon 114–15 Oxyhemoglobin 56–7 Pain 337, 385 Palillia 87 Pallidum 317 Parahippocampal cortex 413, 426 Parahippocampal gyrus 42, 313, 481 Parahippocampal place area 262 Parallel distributed processing 90 Parietal convexity 276 Parietal cortex 27, 31, 171, 216, 276, 334, 426 Parietal-frontal system 365 Parietal lobe 27, 32, 87, 170–1, 175, 216, 286, 334

548

Subject index

Parietal operculum 290 Parietofrontal connections 313 Parietotemporal cortex 295 Parkinson’s disease (PD) 56, 162, 195, 196, 311, 442–3, 446, 450–1, 455–6, 461 Pars opercularis 32, 76 Pars triangularis 31, 76, 290 Pattern associator network 90 Pavlovian conditioning 440 Perceptual categorization 231–44 Perceptual priming 444 Perceptual representation system (PRS) 439, 440, 444–7 Perilesional tissue 139–42, 144 Perirhinal cortex 413, 424, 426 Perisylvian region 53, 67, 68, 77, 80, 103, 130, 141, 143 Personal future 456 Personal past 452, 456 Phobias 492 Phonagnosia 268, 272–3 Phonemic fluency 67 Phonics 116 Phonological lexicon 77, 78, 80, 81, 82, 85–8 Phonological loop 417, 447 Phonological output lexicon 114–15 Phonological processing 35–6, 37, 143 Phonology 105 Phrenology 75 Piaget, J. 337 Pick bodies 483, 484 Pick cells 483 Pick complex 476 Pick’s disease 477, 481, 484, 504 Plasticity brain 137, 144 neural 381 Polar prefrontal cortex 401 Polymorphisms 339 Polysemic words 97–8 Popular culture 5 Porteus Mazes 441 Positron emission tomography (PET) 35–40, 54–9, 130, 139, 187, 216, 268, 275, 308, 336, 351, 412, 446, 448 Postauditory cortex 286 Postcentral gyrus 52, 286, 294 Postcommisural fornix 413 Posterior cingulate region 403 Posterior cortical atrophy 254, 258 Posterior cortical regions 34, 35, 40 Posterior insular cortex 295 Posterior occipital cortex 445 Posterior parietal cortex 39, 252, 287, 308, 313, 318, 364, 426 Posterior parietal lobe 317, 334 Posterior temporal lobe 26, 87 Posterior ventrolateral region 36 Postural errors 165–6 Pragmatic abilities 95, 101–3, 104, 106

Pragmatics 101, 102, 104, 105 Precentral cortex 164 Precentral gyrus 383 Precommisural fornix 383, 413 Prefrontal cortex (PFC) 28, 40, 41, 276, 379–82, 394–404, 414, 418, 426 cognitive and emotional functions of 397–403 and human development 394–7 Prefrontal-hippocampal circuit 428 Premotor cortex 39, 164, 168, 171–3, 180, 216, 314, 318, 382, 387, 389, 403 Primary auditory cortex 79, 80, 90, 269 Primary motor cortex 34, 80, 164, 172, 382–4, 387, 389, 403 Primary somatosensory cortex (SI) 286, 288, 291 Primary visual cortex 252, 253–4, 350, 353–4 Prodigies 18 Proprioception 285, 291, 294, 299 Prosody 95, 96–7, 104, 106, 141, 196, 271–2, 472, 473 emotional 96, 271–2 linguistic 96, 271 Prosopagnosia 253 Protonumeric mechanisms 201 Pseudonaming 244 Psychoanalysis 337 Psycholinguistic Assessment of Language Processing in Aphasia (PALPA) 122, 233 Psychology 2 Psychometry 17–18 Psychopathology 336, 341–3 Pulvinar nucleus 174–5 Putamen 174, 317 Pyramids and Palm Trees Test 238, 240, 476 Radial glia 131 Raven’s Coloured Progressive Matrices (RCPM) 151, 152 Raven’s Progressive Matrices 398 Readiness potential 39 Reading 39–40, 113–16, 122, 131, 207 asemantic route in 207 impairments of 122 letter-by-letter 121–2 Reading models dual-route 114–6, 123 lexical 113 nonlexical 113 sub-word-level 115, 124 Recency effect 448, 449, 458 Redundancy 139 Reduplicative paramnesia 387 Regional cerebral blood flow (rCBF) 53, 54–5, 59, 141 Regularization errors 120 Repetitive transcranial magnetic stimulation (rTMS) 313

Subject index Retrieval 210 active 35–6 automatic 37 episodic 37 lexical 143 semantic 36, 37 strategic 36 verbal 36 Retrograde tracer techniques 32 Retroinsular cortex 286, 287 Retrosplenial area 42, 43 Rhesus monkey 27 Rhinal sulcus 413 Right-handedness 76, 93–4, 105, 140, 164, 168, 170, 171, 176, 179, 180 Rostral intraparietal sulcus 37 Sarcasm 102 Schizophrenia 341, 342 Secondary somatosensory cortex (SII) 286–7, 289, 290, 291 Selection negativity 356 Self-mutilation 343 Self-regulation 331, 336–43, 379, 387, 389, 397 Semantic coding 99 Semantic-conceptual field, see Conceptualsemantic field Semantic dementia 471–85 neuropathological features of 483–5 and primary progressive aphasia 476–80 and vocabulary 474–5 Semantic elaboration 212 Semantic fluency 67 Semantic judgment 65, 140 Semantic processing 67, 95, 100, 104, 106 Semantic system 114 Sensory motor paradox 288 Silver-staining method 27 Simultanagnosia 203, 255–7 dorsal 256–7 ventral 256–7 Singing 185–97 Single-photon emission computerized tomography (SPECT) 53, 55–6, 497, 499 Single-photon emission tomography (SPET) 308 Size judgment 216 Social cognition 401–3 Social judgment 387, 392, 396, 403 Social learning theory 337 Socialization 336, 338 Somaesthetic recognition disorders 285–99 Somatoparaphrenia 316, 317 Somatosensory cortex 286 Somatosensory disorders 291, 294 Somatosensory long-term memory system (LTM) 296 Somatosensory short-term memory system (STM) 296 Spatial attentional processing 31, 312

549

Spatial neglect 95–6, 308 unilateral 307, 308, 313, 314, 316 Speech fluency of 76 loss of 75–6 Speech akinesia 85–6, 87 Speech disturbances 52 Speech impairment 76 Speech production 34, 38–9 Spelling, dual-route models of 116–18, 123 Spinal cord 161, 172, 180, 285, 384 Splenium 118, 121 Split-brain patients 94 Statistical analysis 62–3 Steady-state evoked potentials (SSEPs) 350 Stem-completion tasks 140, 142, 445, 446 Stimulus boundedness 386–7 Stress emphatic 96 lexical 96–7 Striate cortex 354 Striatum 393, 443 Stroke 18, 76, 113, 122, 308, 313, 386, 414, 420, 421 Stroop effect 336, 338, 339 Structural description 446–7 Stuttering 194 Subcallosal gyrus 383, 385, 391 Subcortical neglect 307–22 cognitive specificity of 313–18 Subcortical temporal region 152 Subiculum 413 Subitizing 202–4, 220 Subsequent memory effect 426 Substantia innominata 383, 414 Subtraction experiments 61–2, 64, 139 Superior colliculus 313, 315 Superior frontal gyrus 390 Superior mesial cortex 387, 391 Superior temporal cortex 318, 403 Superior temporal gyrus 27, 29, 31, 33, 34–5, 36, 37, 38, 40, 41, 42, 43, 78, 80, 314 Superior temporal lobe 76, 77, 87 Superior temporal sulcus 27, 29, 31, 33–5, 36, 37, 40, 41, 42, 273, 401 Supplementary motor area 40, 168, 172–3, 383, 384, 390 Supplementary motor cortex 34, 39, 40, 389 Supramarginal gyrus 32, 34, 35, 37, 40, 142, 143, 171, 287, 311, 314 Sylvian fissure 27–9, 31, 32, 37, 287 Synaptogenesis 138 Syntactical errors 206 Tactile perception 291–2 Temporal cortex 27 Temporal gyri 254, 481 Temporal judgment 216 Temporal limbic regions 42 Temporal lobe 19, 27, 87, 180, 384, 454, 481–2

550

Subject index

Temporal lobectomy 419 Temporal-parietal junction 179, 311, 341 Temporal polar cortex 401 Temporal pole 67, 393, 483 Temporal processing 131–2, 270–1, 278 Temporal proisocortex 30, 41 Temporofrontal fibers 31 Temporoparietal junction 130, 314 Temporoparietal-occipital region 151 Testosterone 130, 131 Thalamotomy 311 Thalamus 79, 85, 128–30, 132, 174–5, 308–13, 315, 317, 319, 384, 385, 393, 413, 414, 420 “Theory of mind” 19, 103, 402–4 Tip-of-the-tongue experiences 453 Token Test 7, 10, 141, 151, 152, 448 Transcoding 205–10, 219 code intrusion errors in 209–10 Transcranial magnetic stimulation 165 Tremor 161 Triple code model 212 Twin studies 339 Uncinate fasciculus 30, 31, 41–2 Utilization behavior 390–1 Ventral frontal region 383 Ventral posterior nuclear complex (VP) 285–6 Ventral prefrontal region 385, 418 Ventral premotor cortex 34, 37, 216, 289 Ventrolateral areas 30 Ventrolateral prefrontal cortex 31, 35, 36, 384, 386 Ventromedial limbic pathways 42–3 Ventromedial prefrontal cortex 483 Ventro-postero-inferior nucleus (VPI) 285–6 Ventro-postero-lateral nucleus (VPL) 285–6 Ventro-postero-medial nucleus (VPM) 285–6 Ventro-postero-superior nucleus (VPS) 285–6

Verb-generation task 139, 140 Verbal associate tasks 36 Verbal communication impairments 104 Verbal deafness 12 Verbal Fluency Test (VFT) 36, 98, 494, 499, 500, 502 Verbal retrieval 36 Verbal semantic system 218 Vicariation 139 Visual neglect 317, 320–1 extrapersonal 314, 315, 317 Visual pathways 353 Visual processing 249 Visuospatial sketchpad 417, 447, 450 Voice recognition 273 Vygotsky, L. S. 337 WAIS Block design 441 Wechsler IQ scales 398 Wernicke–Korsakoff syndrome 414 Wernicke–Kussmaul–Lichtheim model 3, 85–91 Wernicke–Lichtheim model 1, 90, 307 Wernicke’s arc 80 Wernicke’s area 26, 31, 34, 42, 57, 67, 78, 79, 80, 82, 83, 90, 118, 119, 141, 170, 269 Wernicke’s information-processing model 77–9, 89, 90–1 White matter 27, 29, 32, 40, 41, 169, 170, 174, 254, 269, 308–10, 313, 314, 317, 319, 321, 322, 387, 390, 392, 393, 418 changes in 418, 427 deep 384, 387 Word comprehension 269 Word generation 67 Word intelligibility index 191 Word-naming 98 Word production 98, 189 Writing 39